Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> 0 were not able to fit
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x5648155d1970>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x5648155d1970>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # ℹ 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure mod… -0.575 0.507 -1.13 -1.57 0.418 0.257
#> 2 age, Cure model 0.00981 0.0103 0.954 -0.0103 0.0300 0.340
#> 3 grade_ii, Cure model 0.109 0.377 0.288 -0.631 0.848 0.774
#> 4 grade_iii, Cure model 0.824 0.388 2.12 0.0637 1.58 0.0337
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00887 -0.295 -0.0200 0.0148 0.768
#> 2 grade_ii, Survival mo… 0.570 0.266 2.14 0.0486 1.09 0.0321
#> 3 grade_iii, Survival m… 0.346 0.248 1.40 -0.139 0.831 0.162
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2568833428 0.0001057233 0.1424774477 0.1504490269
#>
#> $b_sd
#> [1] 0.50683660 0.01028218 0.37746185 0.38787759
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1344939 0.9544172 0.2875586 2.1241216
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.25658743 0.33987249 0.77368463 0.03365997
#>
#> $beta_var
#> [1] 0.0000787033 0.0706357168 0.0613044457
#>
#> $beta_sd
#> [1] 0.008871488 0.265773808 0.247597346
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.2948899 2.1428175 1.3969616
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.76807802 0.03212775 0.16242513
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01121437 0.54634795 0.64298863
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.55926985 0.03073031 -0.26951211
#> grade_iii, Cure model
#> 1.19919893
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 153 21.33 1 55 1 0
#> 59 10.16 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 150 20.33 1 48 0 0
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 111 17.45 1 47 0 1
#> 128 20.35 1 35 0 1
#> 177 12.53 1 75 0 0
#> 179 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 139 21.49 1 63 1 0
#> 57 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 63.1 22.77 1 31 1 0
#> 181 16.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 111.1 17.45 1 47 0 1
#> 99 21.19 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 56 12.21 1 60 0 0
#> 8 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 88 18.37 1 47 0 0
#> 79 16.23 1 54 1 0
#> 59.1 10.16 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 56.1 12.21 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 111.2 17.45 1 47 0 1
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 181.1 16.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 101 9.97 1 10 0 1
#> 134.1 17.81 1 47 1 0
#> 90 20.94 1 50 0 1
#> 8.1 18.43 1 32 0 0
#> 114 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 130.1 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 8.2 18.43 1 32 0 0
#> 24.1 23.89 1 38 0 0
#> 114.1 13.68 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 93 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 188.1 16.16 1 46 0 1
#> 114.2 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 184 17.77 1 38 0 0
#> 117 17.46 1 26 0 1
#> 170 19.54 1 43 0 1
#> 111.3 17.45 1 47 0 1
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 181.2 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 169.2 22.41 1 46 0 0
#> 169.3 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 133.1 14.65 1 57 0 0
#> 179.1 18.63 1 42 0 0
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 124.1 9.73 1 NA 1 0
#> 194.2 22.40 1 38 0 1
#> 188.2 16.16 1 46 0 1
#> 42.1 12.43 1 49 0 1
#> 166.1 19.98 1 48 0 0
#> 51 18.23 1 83 0 1
#> 4.1 17.64 1 NA 0 1
#> 127 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 57.1 14.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 166.2 19.98 1 48 0 0
#> 36 21.19 1 48 0 1
#> 127.1 3.53 1 62 0 1
#> 195 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 55.1 19.34 1 69 0 1
#> 133.2 14.65 1 57 0 0
#> 66.1 22.13 1 53 0 0
#> 77 7.27 1 67 0 1
#> 123 13.00 1 44 1 0
#> 190 20.81 1 42 1 0
#> 187.1 9.92 1 39 1 0
#> 123.1 13.00 1 44 1 0
#> 134.2 17.81 1 47 1 0
#> 57.2 14.46 1 45 0 1
#> 114.3 13.68 1 NA 0 0
#> 16.1 8.71 1 71 0 1
#> 101.1 9.97 1 10 0 1
#> 167 15.55 1 56 1 0
#> 39 15.59 1 37 0 1
#> 44 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 87.1 24.00 0 27 0 0
#> 102 24.00 0 49 0 0
#> 119 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 87.2 24.00 0 27 0 0
#> 112 24.00 0 61 0 0
#> 174 24.00 0 49 1 0
#> 119.1 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 174.1 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 156 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 44.1 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 11 24.00 0 42 0 1
#> 104.1 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 75.1 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 71 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 178 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 165.1 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 112.1 24.00 0 61 0 0
#> 64 24.00 0 43 0 0
#> 118 24.00 0 44 1 0
#> 2.2 24.00 0 9 0 0
#> 20 24.00 0 46 1 0
#> 3 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 83.2 24.00 0 6 0 0
#> 144.2 24.00 0 28 0 1
#> 122 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 54.1 24.00 0 53 1 0
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 83.3 24.00 0 6 0 0
#> 102.2 24.00 0 49 0 0
#> 20.1 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 144.3 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 83.4 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 103.1 24.00 0 56 1 0
#> 65 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 178.1 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 87.3 24.00 0 27 0 0
#> 2.3 24.00 0 9 0 0
#> 44.2 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.56 NA NA NA
#> 2 age, Cure model 0.0307 NA NA NA
#> 3 grade_ii, Cure model -0.270 NA NA NA
#> 4 grade_iii, Cure model 1.20 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0112 NA NA NA
#> 2 grade_ii, Survival model 0.546 NA NA NA
#> 3 grade_iii, Survival model 0.643 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.55927 0.03073 -0.26951 1.19920
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.8
#> Residual Deviance: 231.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.55926985 0.03073031 -0.26951211 1.19919893
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01121437 0.54634795 0.64298863
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7982916 0.8719429 0.5371331 0.7923657 0.6054352 0.9809174 0.6484935
#> [8] 0.7687552 0.5963900 0.9135684 0.6789637 0.4185613 0.5145250 0.8909059
#> [15] 0.2850273 0.4880813 0.6143850 0.4185613 0.9482325 0.9439718 0.8421114
#> [22] 0.2850273 0.8209726 0.8767553 0.7687552 0.5480480 0.9135684 0.9311059
#> [29] 0.6936738 0.7364223 0.7153259 0.8368556 0.3502400 0.9311059 0.7687552
#> [36] 0.9566182 0.8041312 0.8209726 0.1074066 0.8098866 0.9397021 0.6484935
#> [43] 0.9607425 0.7364223 0.5680181 0.6936738 0.5870886 0.8098866 0.5016654
#> [50] 0.6936738 0.1074066 0.3286881 0.9524476 0.5145250 0.8421114 0.6714702
#> [57] 0.7558411 0.7623404 0.6400570 0.7687552 0.2554971 0.4608279 0.8209726
#> [64] 0.3502400 0.3502400 0.3502400 0.9224328 0.8767553 0.6789637 0.9769334
#> [71] 0.9688946 0.4185613 0.8421114 0.9224328 0.6143850 0.7225661 0.9925039
#> [78] 0.8571681 0.8909059 0.7295391 0.6143850 0.5480480 0.9925039 0.2063643
#> [85] 0.6484935 0.8767553 0.4608279 0.9886671 0.9045891 0.5776923 0.9688946
#> [92] 0.9045891 0.7364223 0.8909059 0.9809174 0.9607425 0.8670770 0.8621493
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 106 18 153 23 150 16 58 111 128 177 179 194 139
#> 16.67 15.21 21.33 16.92 20.33 8.71 19.34 17.45 20.35 12.53 18.63 22.40 21.49
#> 57 63 175 166 194.1 52 10 188 63.1 181 133 111.1 99
#> 14.46 22.77 21.91 19.98 22.40 10.42 10.53 16.16 22.77 16.46 14.65 17.45 21.19
#> 177.1 56 8 134 88 79 169 56.1 111.2 145 171 181.1 24
#> 12.53 12.21 18.43 17.81 18.37 16.23 22.41 12.21 17.45 10.07 16.57 16.46 23.89
#> 130 49 55 101 134.1 90 8.1 68 130.1 136 8.2 24.1 15
#> 16.47 12.19 19.34 9.97 17.81 20.94 18.43 20.62 16.47 21.83 18.43 23.89 22.68
#> 93 139.1 188.1 97 184 117 170 111.3 164 66 181.2 169.1 169.2
#> 10.33 21.49 16.16 19.14 17.77 17.46 19.54 17.45 23.60 22.13 16.46 22.41 22.41
#> 169.3 42 133.1 179.1 183 187 194.2 188.2 42.1 166.1 51 127 26
#> 22.41 12.43 14.65 18.63 9.24 9.92 22.40 16.16 12.43 19.98 18.23 3.53 15.77
#> 57.1 40 166.2 36 127.1 78 55.1 133.2 66.1 77 123 190 187.1
#> 14.46 18.00 19.98 21.19 3.53 23.88 19.34 14.65 22.13 7.27 13.00 20.81 9.92
#> 123.1 134.2 57.2 16.1 101.1 167 39 44 165 87 121 87.1 102
#> 13.00 17.81 14.46 8.71 9.97 15.55 15.59 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 137 191 87.2 112 174 119.1 173 54 174.1 27 2 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 156 144.1 44.1 62 2.1 48 75 104 193 11 104.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 103 71 83 53 178 147 160 19 165.1 121.1 27.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 64 118 2.2 20 3 83.1 176 83.2 144.2 122 11.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 151 47 83.3 102.2 20.1 163 144.3 80 35 162 146 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.4 152 103.1 65 28 172 151.1 46 12 178.1 67 87.3 2.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.2 142 74
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003068964 0.412259046 0.513073506
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.23785323 0.02510017 0.34639496
#> grade_iii, Cure model
#> 0.64936671
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 180 14.82 1 37 0 0
#> 192 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 111 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 169 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 169.1 22.41 1 46 0 0
#> 79 16.23 1 54 1 0
#> 130 16.47 1 53 0 1
#> 183 9.24 1 67 1 0
#> 190 20.81 1 42 1 0
#> 113 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 187 9.92 1 39 1 0
#> 77 7.27 1 67 0 1
#> 51 18.23 1 83 0 1
#> 155 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 30 17.43 1 78 0 0
#> 88 18.37 1 47 0 0
#> 97 19.14 1 65 0 1
#> 155.1 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 42.1 12.43 1 49 0 1
#> 117 17.46 1 26 0 1
#> 189 10.51 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 77.1 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 66 22.13 1 53 0 0
#> 168 23.72 1 70 0 0
#> 189.1 10.51 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 150 20.33 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 58 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 134 17.81 1 47 1 0
#> 13 14.34 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 117.1 17.46 1 26 0 1
#> 169.2 22.41 1 46 0 0
#> 192.1 16.44 1 31 1 0
#> 169.3 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 81.2 14.06 1 34 0 0
#> 175 21.91 1 43 0 0
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 57.1 14.46 1 45 0 1
#> 93.1 10.33 1 52 0 1
#> 70 7.38 1 30 1 0
#> 158.1 20.14 1 74 1 0
#> 26.1 15.77 1 49 0 1
#> 99 21.19 1 38 0 1
#> 166 19.98 1 48 0 0
#> 37 12.52 1 57 1 0
#> 117.2 17.46 1 26 0 1
#> 13.1 14.34 1 54 0 1
#> 111.1 17.45 1 47 0 1
#> 39 15.59 1 37 0 1
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 188 16.16 1 46 0 1
#> 63 22.77 1 31 1 0
#> 30.1 17.43 1 78 0 0
#> 184.1 17.77 1 38 0 0
#> 97.1 19.14 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 18.1 15.21 1 49 1 0
#> 167.1 15.55 1 56 1 0
#> 40 18.00 1 28 1 0
#> 99.1 21.19 1 38 0 1
#> 145.1 10.07 1 65 1 0
#> 68 20.62 1 44 0 0
#> 195.1 11.76 1 NA 1 0
#> 150.2 20.33 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 90.1 20.94 1 50 0 1
#> 164 23.60 1 76 0 1
#> 58.1 19.34 1 39 0 0
#> 159.1 10.55 1 50 0 1
#> 129 23.41 1 53 1 0
#> 164.1 23.60 1 76 0 1
#> 93.2 10.33 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 16.1 8.71 1 71 0 1
#> 157 15.10 1 47 0 0
#> 55 19.34 1 69 0 1
#> 190.1 20.81 1 42 1 0
#> 154 12.63 1 20 1 0
#> 16.2 8.71 1 71 0 1
#> 127 3.53 1 62 0 1
#> 63.1 22.77 1 31 1 0
#> 190.2 20.81 1 42 1 0
#> 157.1 15.10 1 47 0 0
#> 81.3 14.06 1 34 0 0
#> 73 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 122 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 73.1 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 102 24.00 0 49 0 0
#> 200 24.00 0 64 0 0
#> 104 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 132.1 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 19 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 122.1 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 109 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 182.1 24.00 0 35 0 0
#> 185 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 20.1 24.00 0 46 1 0
#> 94.1 24.00 0 51 0 1
#> 82 24.00 0 34 0 0
#> 19.1 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 185.1 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 178.1 24.00 0 52 1 0
#> 102.1 24.00 0 49 0 0
#> 144.1 24.00 0 28 0 1
#> 126 24.00 0 48 0 0
#> 144.2 24.00 0 28 0 1
#> 118 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 142.1 24.00 0 53 0 0
#> 102.2 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 67.1 24.00 0 25 0 0
#> 38.1 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 156 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 72.1 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 104.1 24.00 0 50 1 0
#> 144.3 24.00 0 28 0 1
#> 161.1 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 19.2 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 21.1 24.00 0 47 0 0
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 71 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 182.2 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 182.3 24.00 0 35 0 0
#> 191.1 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.24 NA NA NA
#> 2 age, Cure model 0.0251 NA NA NA
#> 3 grade_ii, Cure model 0.346 NA NA NA
#> 4 grade_iii, Cure model 0.649 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00307 NA NA NA
#> 2 grade_ii, Survival model 0.412 NA NA NA
#> 3 grade_iii, Survival model 0.513 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2379 0.0251 0.3464 0.6494
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.23785323 0.02510017 0.34639496 0.64936671
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003068964 0.412259046 0.513073506
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.867374579 0.138993248 0.753438372 0.712059676 0.575691009 0.007841835
#> [7] 0.558023736 0.914855195 0.513024377 0.835220326 0.149993330 0.678691979
#> [13] 0.149993330 0.593158301 0.548987881 0.930590935 0.275484841 0.106307322
#> [19] 0.875424985 0.922734465 0.969311801 0.438651969 0.794278489 0.627841238
#> [25] 0.670249359 0.530941284 0.429006244 0.409988464 0.794278489 0.720475315
#> [31] 0.938432210 0.835220326 0.485967462 0.082343528 0.969311801 0.786030489
#> [37] 0.094661922 0.899080658 0.190855379 0.024123005 0.753438372 0.558023736
#> [43] 0.984660204 0.323176078 0.593158301 0.653422917 0.381311420 0.467185712
#> [49] 0.457740784 0.737033365 0.323176078 0.485967462 0.149993330 0.575691009
#> [55] 0.149993330 0.255572347 0.753438372 0.202110419 0.619151889 0.352119212
#> [61] 0.720475315 0.875424985 0.961562636 0.352119212 0.627841238 0.234966216
#> [67] 0.371470686 0.818939956 0.485967462 0.737033365 0.513024377 0.644894769
#> [73] 0.213443626 0.851363143 0.610483002 0.118081703 0.530941284 0.467185712
#> [79] 0.409988464 0.818939956 0.678691979 0.653422917 0.448235581 0.234966216
#> [85] 0.899080658 0.303822748 0.323176078 0.213443626 0.255572347 0.043492082
#> [91] 0.381311420 0.851363143 0.068934148 0.043492082 0.875424985 0.303822748
#> [97] 0.938432210 0.695348935 0.381311420 0.275484841 0.810714894 0.938432210
#> [103] 0.992341395 0.118081703 0.275484841 0.695348935 0.753438372 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 10 15 81 180 192 24 181 101 111 42 169 18 169.1
#> 10.53 22.68 14.06 14.82 16.44 23.89 16.46 9.97 17.45 12.43 22.41 15.21 22.41
#> 79 130 183 190 113 93 187 77 51 155 26 29 30
#> 16.23 16.47 9.24 20.81 22.86 10.33 9.92 7.27 18.23 13.08 15.77 15.45 17.43
#> 88 97 155.1 57 16 42.1 117 69 77.1 60 92 145 66
#> 18.37 19.14 13.08 14.46 8.71 12.43 17.46 23.23 7.27 13.15 22.92 10.07 22.13
#> 168 81.1 181.1 91 150 79.1 167 58 184 134 13 150.1 117.1
#> 23.72 14.06 16.46 5.33 20.33 16.23 15.55 19.34 17.77 17.81 14.34 20.33 17.46
#> 169.2 192.1 169.3 90 81.2 175 100 158 57.1 93.1 70 158.1 26.1
#> 22.41 16.44 22.41 20.94 14.06 21.91 16.07 20.14 14.46 10.33 7.38 20.14 15.77
#> 99 166 37 117.2 13.1 111.1 39 139 159 188 63 30.1 184.1
#> 21.19 19.98 12.52 17.46 14.34 17.45 15.59 21.49 10.55 16.16 22.77 17.43 17.77
#> 97.1 37.1 18.1 167.1 40 99.1 145.1 68 150.2 139.1 90.1 164 58.1
#> 19.14 12.52 15.21 15.55 18.00 21.19 10.07 20.62 20.33 21.49 20.94 23.60 19.34
#> 159.1 129 164.1 93.2 68.1 16.1 157 55 190.1 154 16.2 127 63.1
#> 10.55 23.41 23.60 10.33 20.62 8.71 15.10 19.34 20.81 12.63 8.71 3.53 22.77
#> 190.2 157.1 81.3 161 75 20 182 122 186 116 193 174 102
#> 20.81 15.10 14.06 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 104 132 119 132.1 112 19 142 151 122.1 7 9 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 94 109 186.1 162 67 182.1 185 84 20.1 94.1 82 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 185.1 144 38 2 178.1 102.1 144.1 126 144.2 118 72 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 102.2 3 152 21 67.1 38.1 109.1 95 83 156 82.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 11 104.1 144.3 161.1 196 19.2 135 21.1 33 165 160 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 191 71 74 64 182.2 143 2.1 182.3 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005319537 0.604158759 0.588879712
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.238482385 0.008123409 -0.358156697
#> grade_iii, Cure model
#> 0.384475673
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 167 15.55 1 56 1 0
#> 81 14.06 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 61 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 16 8.71 1 71 0 1
#> 40.1 18.00 1 28 1 0
#> 179 18.63 1 42 0 0
#> 157 15.10 1 47 0 0
#> 175 21.91 1 43 0 0
#> 190 20.81 1 42 1 0
#> 51 18.23 1 83 0 1
#> 52 10.42 1 52 0 1
#> 124.1 9.73 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 23 16.92 1 61 0 0
#> 41 18.02 1 40 1 0
#> 77.1 7.27 1 67 0 1
#> 40.2 18.00 1 28 1 0
#> 26 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 149.2 8.37 1 33 1 0
#> 42 12.43 1 49 0 1
#> 149.3 8.37 1 33 1 0
#> 89.1 11.44 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 129 23.41 1 53 1 0
#> 169 22.41 1 46 0 0
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 89.2 11.44 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 157.1 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 13 14.34 1 54 0 1
#> 113 22.86 1 34 0 0
#> 69 23.23 1 25 0 1
#> 168 23.72 1 70 0 0
#> 79 16.23 1 54 1 0
#> 24 23.89 1 38 0 0
#> 99.1 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 36 21.19 1 48 0 1
#> 164 23.60 1 76 0 1
#> 16.1 8.71 1 71 0 1
#> 52.1 10.42 1 52 0 1
#> 101 9.97 1 10 0 1
#> 100 16.07 1 60 0 0
#> 167.1 15.55 1 56 1 0
#> 8.1 18.43 1 32 0 0
#> 91 5.33 1 61 0 1
#> 175.1 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 133 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 96 14.54 1 33 0 1
#> 199.1 19.81 1 NA 0 1
#> 51.1 18.23 1 83 0 1
#> 91.1 5.33 1 61 0 1
#> 168.1 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 51.2 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 66 22.13 1 53 0 0
#> 89.3 11.44 1 NA 0 0
#> 149.4 8.37 1 33 1 0
#> 30.1 17.43 1 78 0 0
#> 30.2 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 168.2 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 114 13.68 1 NA 0 0
#> 180.1 14.82 1 37 0 0
#> 145.1 10.07 1 65 1 0
#> 113.1 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 180.2 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 4.1 17.64 1 NA 0 1
#> 129.1 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 14 12.89 1 21 0 0
#> 181 16.46 1 45 0 1
#> 187.1 9.92 1 39 1 0
#> 55 19.34 1 69 0 1
#> 114.1 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 123 13.00 1 44 1 0
#> 76.1 19.22 1 54 0 1
#> 188.1 16.16 1 46 0 1
#> 168.3 23.72 1 70 0 0
#> 63.1 22.77 1 31 1 0
#> 123.1 13.00 1 44 1 0
#> 171 16.57 1 41 0 1
#> 90 20.94 1 50 0 1
#> 180.3 14.82 1 37 0 0
#> 6 15.64 1 39 0 0
#> 91.2 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 129.2 23.41 1 53 1 0
#> 169.1 22.41 1 46 0 0
#> 138 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 47 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 80 24.00 0 41 0 0
#> 47.1 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 73 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 48 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 112 24.00 0 61 0 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 104.1 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 156.1 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 54.1 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 173.1 24.00 0 19 0 1
#> 38.1 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 72.1 24.00 0 40 0 1
#> 72.2 24.00 0 40 0 1
#> 44.1 24.00 0 56 0 0
#> 147.1 24.00 0 76 1 0
#> 115 24.00 0 NA 1 0
#> 1 24.00 0 23 1 0
#> 135 24.00 0 58 1 0
#> 143 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 178.1 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 47.2 24.00 0 38 0 1
#> 198 24.00 0 66 0 1
#> 12.1 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 1.1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 98 24.00 0 34 1 0
#> 12.2 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 118.2 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 109.1 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 65.1 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 143.1 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 47.3 24.00 0 38 0 1
#> 27.2 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.238 NA NA NA
#> 2 age, Cure model 0.00812 NA NA NA
#> 3 grade_ii, Cure model -0.358 NA NA NA
#> 4 grade_iii, Cure model 0.384 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00532 NA NA NA
#> 2 grade_ii, Survival model 0.604 NA NA NA
#> 3 grade_iii, Survival model 0.589 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.238482 0.008123 -0.358157 0.384476
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 251.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.238482385 0.008123409 -0.358156697 0.384475673
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005319537 0.604158759 0.588879712
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.644195174 0.755096712 0.958214960 0.846169824 0.453398157 0.916489633
#> [7] 0.916489633 0.899137319 0.453398157 0.382191698 0.662545360 0.245005216
#> [13] 0.309672046 0.413108144 0.828243103 0.681008694 0.330666370 0.540020803
#> [19] 0.443232955 0.958214960 0.453398157 0.625546116 0.491845834 0.341198311
#> [25] 0.916489633 0.810031155 0.916489633 0.392532094 0.109863037 0.211801565
#> [31] 0.501456585 0.800863929 0.764372423 0.855134588 0.662545360 0.736542297
#> [37] 0.267570855 0.745839816 0.167620195 0.144182035 0.047064951 0.588216683
#> [43] 0.005295032 0.267570855 0.156078242 0.267570855 0.095031349 0.899137319
#> [49] 0.828243103 0.872861141 0.616180257 0.644195174 0.392532094 0.975050571
#> [55] 0.245005216 0.881705913 0.717786644 0.361899117 0.727195419 0.413108144
#> [61] 0.975050571 0.047064951 0.413108144 0.569135938 0.233669251 0.916489633
#> [67] 0.501456585 0.501456585 0.482126996 0.047064951 0.597667207 0.681008694
#> [73] 0.855134588 0.167620195 0.530292409 0.681008694 0.018007553 0.190414677
#> [79] 0.320209504 0.109863037 0.819158253 0.791731096 0.578709207 0.881705913
#> [85] 0.341198311 0.549798008 0.773592769 0.361899117 0.597667207 0.047064951
#> [91] 0.190414677 0.773592769 0.559504470 0.298965833 0.681008694 0.634857814
#> [97] 0.975050571 0.033479758 0.109863037 0.211801565 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 167 81 77 61 40 149 149.1 16 40.1 179 157 175 190
#> 15.55 14.06 7.27 10.12 18.00 8.37 8.37 8.71 18.00 18.63 15.10 21.91 20.81
#> 51 52 180 166 23 41 77.1 40.2 26 117 58 149.2 42
#> 18.23 10.42 14.82 19.98 16.92 18.02 7.27 18.00 15.77 17.46 19.34 8.37 12.43
#> 149.3 8 129 169 30 177 60 145 157.1 57 99 13 113
#> 8.37 18.43 23.41 22.41 17.43 12.53 13.15 10.07 15.10 14.46 21.19 14.34 22.86
#> 69 168 79 24 99.1 92 36 164 16.1 52.1 101 100 167.1
#> 23.23 23.72 16.23 23.89 21.19 22.92 21.19 23.60 8.71 10.42 9.97 16.07 15.55
#> 8.1 91 175.1 187 133 76 96 51.1 91.1 168.1 51.2 130 66
#> 18.43 5.33 21.91 9.92 14.65 19.22 14.54 18.23 5.33 23.72 18.23 16.47 22.13
#> 149.4 30.1 30.2 110 168.2 188 180.1 145.1 113.1 45 180.2 78 63
#> 8.37 17.43 17.43 17.56 23.72 16.16 14.82 10.07 22.86 17.42 14.82 23.88 22.77
#> 158 129.1 49 14 181 187.1 55 106 123 76.1 188.1 168.3 63.1
#> 20.14 23.41 12.19 12.89 16.46 9.92 19.34 16.67 13.00 19.22 16.16 23.72 22.77
#> 123.1 171 90 180.3 6 91.2 86 129.2 169.1 138 17 46 2
#> 13.00 16.57 20.94 14.82 15.64 5.33 23.81 23.41 22.41 24.00 24.00 24.00 24.00
#> 160 7 27 22 156 176 173 126 9 19 47 28 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 185 162 67 38 104 48 118 22.1 191 112 147 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 44 102 104.1 72 156.1 176.1 12 35 54 172 142 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 84 173.1 38.1 161.1 72.1 72.2 44.1 147.1 1 135 143 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 178.1 20 47.2 198 12.1 109 1.1 118.1 27.1 102.1 98 12.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 31 118.2 7.1 109.1 116 122 65.1 46.1 143.1 120 2.1 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.3 27.2 152 95
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01178161 0.80281286 0.42525954
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.52957583 0.01535231 -0.10449292
#> grade_iii, Cure model
#> 0.18769368
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 37.1 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 45 17.42 1 54 0 1
#> 40 18.00 1 28 1 0
#> 45.1 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 86 23.81 1 58 0 1
#> 57 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 149 8.37 1 33 1 0
#> 175 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 78 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 166 19.98 1 48 0 0
#> 32 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 158 20.14 1 74 1 0
#> 15 22.68 1 48 0 0
#> 105 19.75 1 60 0 0
#> 99 21.19 1 38 0 1
#> 45.2 17.42 1 54 0 1
#> 55 19.34 1 69 0 1
#> 157 15.10 1 47 0 0
#> 32.1 20.90 1 37 1 0
#> 179 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 37.2 12.52 1 57 1 0
#> 106.1 16.67 1 49 1 0
#> 86.1 23.81 1 58 0 1
#> 16 8.71 1 71 0 1
#> 179.1 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 168 23.72 1 70 0 0
#> 26.1 15.77 1 49 0 1
#> 77 7.27 1 67 0 1
#> 168.1 23.72 1 70 0 0
#> 40.1 18.00 1 28 1 0
#> 106.2 16.67 1 49 1 0
#> 79 16.23 1 54 1 0
#> 42 12.43 1 49 0 1
#> 70.1 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 133 14.65 1 57 0 0
#> 92 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 92.1 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 190 20.81 1 42 1 0
#> 140 12.68 1 59 1 0
#> 130 16.47 1 53 0 1
#> 177 12.53 1 75 0 0
#> 89 11.44 1 NA 0 0
#> 79.1 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 184.1 17.77 1 38 0 0
#> 154.1 12.63 1 20 1 0
#> 169 22.41 1 46 0 0
#> 110 17.56 1 65 0 1
#> 183 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 45.3 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 88.1 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 125 15.65 1 67 1 0
#> 15.1 22.68 1 48 0 0
#> 158.1 20.14 1 74 1 0
#> 166.1 19.98 1 48 0 0
#> 164 23.60 1 76 0 1
#> 130.1 16.47 1 53 0 1
#> 155 13.08 1 26 0 0
#> 55.1 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 130.2 16.47 1 53 0 1
#> 123.1 13.00 1 44 1 0
#> 6 15.64 1 39 0 0
#> 13.1 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 66.1 22.13 1 53 0 0
#> 57.1 14.46 1 45 0 1
#> 70.2 7.38 1 30 1 0
#> 177.1 12.53 1 75 0 0
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 58.1 19.34 1 39 0 0
#> 29 15.45 1 68 1 0
#> 190.1 20.81 1 42 1 0
#> 101 9.97 1 10 0 1
#> 111 17.45 1 47 0 1
#> 114.1 13.68 1 NA 0 0
#> 37.3 12.52 1 57 1 0
#> 25.1 6.32 1 34 1 0
#> 105.1 19.75 1 60 0 0
#> 88.2 18.37 1 47 0 0
#> 114.2 13.68 1 NA 0 0
#> 29.1 15.45 1 68 1 0
#> 13.2 14.34 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 6.1 15.64 1 39 0 0
#> 41 18.02 1 40 1 0
#> 85 16.44 1 36 0 0
#> 149.1 8.37 1 33 1 0
#> 115 24.00 0 NA 1 0
#> 137 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 138 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 178 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 71.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 17 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 132 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 185 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 137.1 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 200.1 24.00 0 64 0 0
#> 47 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 38.1 24.00 0 31 1 0
#> 137.2 24.00 0 45 1 0
#> 165.1 24.00 0 47 0 0
#> 54.1 24.00 0 53 1 0
#> 9.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 137.3 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 104 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 34.1 24.00 0 36 0 0
#> 38.2 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 137.4 24.00 0 45 1 0
#> 115.1 24.00 0 NA 1 0
#> 103.1 24.00 0 56 1 0
#> 98.1 24.00 0 34 1 0
#> 119 24.00 0 17 0 0
#> 27.1 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 27.2 24.00 0 63 1 0
#> 191.1 24.00 0 60 0 1
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 33 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 103.2 24.00 0 56 1 0
#> 118 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 73.1 24.00 0 NA 0 1
#> 182 24.00 0 35 0 0
#> 28 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 17.1 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 174.1 24.00 0 49 1 0
#> 94.2 24.00 0 51 0 1
#> 198.1 24.00 0 66 0 1
#> 200.2 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.530 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model -0.104 NA NA NA
#> 4 grade_iii, Cure model 0.188 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0118 NA NA NA
#> 2 grade_ii, Survival model 0.803 NA NA NA
#> 3 grade_iii, Survival model 0.425 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52958 0.01535 -0.10449 0.18769
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 256.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52957583 0.01535231 -0.10449292 0.18769368
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01178161 0.80281286 0.42525954
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8015747433 0.8015747433 0.6841561793 0.4045282769 0.3440773671
#> [6] 0.4045282769 0.4449785008 0.0046503482 0.6627892224 0.1157092511
#> [11] 0.9796294537 0.9177675245 0.0886507050 0.8859330778 0.0008845186
#> [16] 0.9386747731 0.2012894031 0.1427505652 0.5471613719 0.1845239283
#> [21] 0.0502541806 0.2186810526 0.1248817720 0.4045282769 0.2368035730
#> [26] 0.6414025622 0.1427505652 0.2735331140 0.7271404793 0.2930909544
#> [31] 0.5575841486 0.8015747433 0.4449785008 0.0046503482 0.9071286705
#> [36] 0.2735331140 0.1064137968 0.0118012917 0.5575841486 0.9692835965
#> [41] 0.0118012917 0.3440773671 0.4449785008 0.5265571841 0.8432681452
#> [46] 0.9386747731 0.3638111965 0.0886507050 0.6520530078 0.0300703817
#> [51] 0.7593456544 0.0300703817 0.3231937248 0.1596836762 0.7485705012
#> [56] 0.4751491860 0.7802925907 0.5265571841 0.6098460546 0.3638111965
#> [61] 0.7593456544 0.0643421233 0.3839392298 0.8965317212 0.1759950597
#> [66] 0.4045282769 0.1248817720 0.2930909544 0.0722036573 0.2368035730
#> [71] 0.5783433891 0.0502541806 0.1845239283 0.2012894031 0.0228628102
#> [76] 0.4751491860 0.7162388689 0.2368035730 0.8539094335 0.4751491860
#> [81] 0.7271404793 0.5888152998 0.6841561793 0.0435258576 0.0722036573
#> [86] 0.6627892224 0.9386747731 0.7802925907 0.8645845517 0.5056703893
#> [91] 0.2368035730 0.6204253936 0.1596836762 0.8752822414 0.3942175410
#> [96] 0.8015747433 0.9796294537 0.2186810526 0.2930909544 0.6204253936
#> [101] 0.6841561793 0.5888152998 0.3336997487 0.5160772594 0.9177675245
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 37 37.1 13 45 40 45.1 106 86 57 153 25 149 175
#> 12.52 12.52 14.34 17.42 18.00 17.42 16.67 23.81 14.46 21.33 6.32 8.37 21.91
#> 187 78 70 166 32 188 158 15 105 99 45.2 55 157
#> 9.92 23.88 7.38 19.98 20.90 16.16 20.14 22.68 19.75 21.19 17.42 19.34 15.10
#> 32.1 179 123 88 26 37.2 106.1 86.1 16 179.1 197 168 26.1
#> 20.90 18.63 13.00 18.37 15.77 12.52 16.67 23.81 8.71 18.63 21.60 23.72 15.77
#> 77 168.1 40.1 106.2 79 42 70.1 184 175.1 133 92 154 92.1
#> 7.27 23.72 18.00 16.67 16.23 12.43 7.38 17.77 21.91 14.65 22.92 12.63 22.92
#> 51 190 140 130 177 79.1 167 184.1 154.1 169 110 183 150
#> 18.23 20.81 12.68 16.47 12.53 16.23 15.55 17.77 12.63 22.41 17.56 9.24 20.33
#> 45.3 36 88.1 66 58 125 15.1 158.1 166.1 164 130.1 155 55.1
#> 17.42 21.19 18.37 22.13 19.34 15.65 22.68 20.14 19.98 23.60 16.47 13.08 19.34
#> 43 130.2 123.1 6 13.1 63 66.1 57.1 70.2 177.1 52 181 58.1
#> 12.10 16.47 13.00 15.64 14.34 22.77 22.13 14.46 7.38 12.53 10.42 16.46 19.34
#> 29 190.1 101 111 37.3 25.1 105.1 88.2 29.1 13.2 6.1 41 85
#> 15.45 20.81 9.97 17.45 12.52 6.32 19.75 18.37 15.45 14.34 15.64 18.02 16.44
#> 149.1 137 196 138 53 178 103 9 80 193 71 34 161
#> 8.37 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 116 71.1 121 200 17 20 35 3 19.1 72 132 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 185 62 31 137.1 31.1 191 165 131 102 54 84 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 200.1 47 27 38.1 137.2 165.1 54.1 9.1 141 47.1 174 137.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 104 135 98 34.1 38.2 80.1 137.4 103.1 98.1 119 27.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.2 191.1 21 126 33 146 103.2 118 7 11 182 28 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 48 151.1 174.1 94.2 198.1 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001060423 0.528410939 0.495688969
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.72591954 0.02732553 0.85970175
#> grade_iii, Cure model
#> 1.03976069
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 123 13.00 1 44 1 0
#> 26 15.77 1 49 0 1
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 30.1 17.43 1 78 0 0
#> 69 23.23 1 25 0 1
#> 39 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 57 14.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 117 17.46 1 26 0 1
#> 197 21.60 1 69 1 0
#> 177 12.53 1 75 0 0
#> 41 18.02 1 40 1 0
#> 199.1 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 183 9.24 1 67 1 0
#> 157 15.10 1 47 0 0
#> 41.1 18.02 1 40 1 0
#> 192 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 136 21.83 1 43 0 1
#> 192.1 16.44 1 31 1 0
#> 153 21.33 1 55 1 0
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 171 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 164 23.60 1 76 0 1
#> 140 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 6 15.64 1 39 0 0
#> 197.1 21.60 1 69 1 0
#> 192.2 16.44 1 31 1 0
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 50.1 10.02 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 158 20.14 1 74 1 0
#> 190 20.81 1 42 1 0
#> 23 16.92 1 61 0 0
#> 153.1 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 91 5.33 1 61 0 1
#> 110.1 17.56 1 65 0 1
#> 117.1 17.46 1 26 0 1
#> 41.2 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 79 16.23 1 54 1 0
#> 78 23.88 1 43 0 0
#> 164.1 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 57.1 14.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 129.1 23.41 1 53 1 0
#> 114 13.68 1 NA 0 0
#> 140.1 12.68 1 59 1 0
#> 66 22.13 1 53 0 0
#> 188.1 16.16 1 46 0 1
#> 40 18.00 1 28 1 0
#> 18.1 15.21 1 49 1 0
#> 111.1 17.45 1 47 0 1
#> 128 20.35 1 35 0 1
#> 41.3 18.02 1 40 1 0
#> 52.1 10.42 1 52 0 1
#> 15.1 22.68 1 48 0 0
#> 57.2 14.46 1 45 0 1
#> 123.1 13.00 1 44 1 0
#> 99 21.19 1 38 0 1
#> 32.1 20.90 1 37 1 0
#> 155 13.08 1 26 0 0
#> 58 19.34 1 39 0 0
#> 188.2 16.16 1 46 0 1
#> 183.1 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 128.1 20.35 1 35 0 1
#> 183.2 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 111.2 17.45 1 47 0 1
#> 106 16.67 1 49 1 0
#> 181 16.46 1 45 0 1
#> 77.1 7.27 1 67 0 1
#> 29 15.45 1 68 1 0
#> 70 7.38 1 30 1 0
#> 52.2 10.42 1 52 0 1
#> 78.1 23.88 1 43 0 0
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 8 18.43 1 32 0 0
#> 127 3.53 1 62 0 1
#> 90.1 20.94 1 50 0 1
#> 77.2 7.27 1 67 0 1
#> 6.1 15.64 1 39 0 0
#> 85 16.44 1 36 0 0
#> 107.1 11.18 1 54 1 0
#> 111.3 17.45 1 47 0 1
#> 58.1 19.34 1 39 0 0
#> 58.2 19.34 1 39 0 0
#> 15.2 22.68 1 48 0 0
#> 35 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 160.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 33 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 80 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 11 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 198 24.00 0 66 0 1
#> 109.1 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 165 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 193.1 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 82.1 24.00 0 34 0 0
#> 38.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 193.2 24.00 0 45 0 1
#> 35.2 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 119 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 9 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 28 24.00 0 67 1 0
#> 191 24.00 0 60 0 1
#> 172 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 67 24.00 0 25 0 0
#> 84.2 24.00 0 39 0 1
#> 143 24.00 0 51 0 0
#> 109.2 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 131 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 38.2 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 182 24.00 0 35 0 0
#> 182.1 24.00 0 35 0 0
#> 182.2 24.00 0 35 0 0
#> 152.1 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 138.1 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 3.2 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 172.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 112 24.00 0 61 0 0
#> 44.2 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 118 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.73 NA NA NA
#> 2 age, Cure model 0.0273 NA NA NA
#> 3 grade_ii, Cure model 0.860 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00106 NA NA NA
#> 2 grade_ii, Survival model 0.528 NA NA NA
#> 3 grade_iii, Survival model 0.496 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.72592 0.02733 0.85970 1.03976
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 251 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.72591954 0.02732553 0.85970175 1.03976069
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001060423 0.528410939 0.495688969
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.46151955 0.85823815 0.74148763 0.62487139 0.62487139 0.14864443
#> [7] 0.76403903 0.32348713 0.80105030 0.36547617 0.57649280 0.26572707
#> [13] 0.89309615 0.50772650 0.73390623 0.48000016 0.90003845 0.42393189
#> [19] 0.94075304 0.79367480 0.50772650 0.67312579 0.49847688 0.25290227
#> [25] 0.67312579 0.30130577 0.77899894 0.65717483 0.59310238 0.08882796
#> [31] 0.87226434 0.55959260 0.74902599 0.26572707 0.67312579 0.90695203
#> [37] 0.83695812 0.18937128 0.41441054 0.38540556 0.64099608 0.30130577
#> [43] 0.16241199 0.17622168 0.88615796 0.98691301 0.55959260 0.57649280
#> [49] 0.50772650 0.12092525 0.92060172 0.70369227 0.02334948 0.08882796
#> [55] 0.71141033 0.23969703 0.82263984 0.96730844 0.80105030 0.82263984
#> [61] 0.83695812 0.12092525 0.87226434 0.22652431 0.71141033 0.54219821
#> [67] 0.77899894 0.59310238 0.39534056 0.50772650 0.92060172 0.18937128
#> [73] 0.80105030 0.85823815 0.32348713 0.36547617 0.85112392 0.43346646
#> [79] 0.71141033 0.94075304 0.46151955 0.06650177 0.39534056 0.94075304
#> [85] 0.34483712 0.59310238 0.64911622 0.66517733 0.96730844 0.77153995
#> [91] 0.96065713 0.92060172 0.02334948 0.28947070 0.55093753 0.48923561
#> [97] 0.99346808 0.34483712 0.96730844 0.74902599 0.67312579 0.90695203
#> [103] 0.59310238 0.43346646 0.43346646 0.18937128 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 76 123 26 30 30.1 69 39 36 57 32 117 197 177
#> 19.22 13.00 15.77 17.43 17.43 23.23 15.59 21.19 14.46 20.90 17.46 21.60 12.53
#> 41 100 97 43 105 183 157 41.1 192 88 136 192.1 153
#> 18.02 16.07 19.14 12.10 19.75 9.24 15.10 18.02 16.44 18.37 21.83 16.44 21.33
#> 18 171 111 164 140 110 6 197.1 192.2 107 60 15 158
#> 15.21 16.57 17.45 23.60 12.68 17.56 15.64 21.60 16.44 11.18 13.15 22.68 20.14
#> 190 23 153.1 113 63 154 91 110.1 117.1 41.2 129 52 79
#> 20.81 16.92 21.33 22.86 22.77 12.63 5.33 17.56 17.46 18.02 23.41 10.42 16.23
#> 78 164.1 188 175 13 77 57.1 13.1 60.1 129.1 140.1 66 188.1
#> 23.88 23.60 16.16 21.91 14.34 7.27 14.46 14.34 13.15 23.41 12.68 22.13 16.16
#> 40 18.1 111.1 128 41.3 52.1 15.1 57.2 123.1 99 32.1 155 58
#> 18.00 15.21 17.45 20.35 18.02 10.42 22.68 14.46 13.00 21.19 20.90 13.08 19.34
#> 188.2 183.1 76.1 86 128.1 183.2 90 111.2 106 181 77.1 29 70
#> 16.16 9.24 19.22 23.81 20.35 9.24 20.94 17.45 16.67 16.46 7.27 15.45 7.38
#> 52.2 78.1 139 134 8 127 90.1 77.2 6.1 85 107.1 111.3 58.1
#> 10.42 23.88 21.49 17.81 18.43 3.53 20.94 7.27 15.64 16.44 11.18 17.45 19.34
#> 58.2 15.2 35 160 75 160.1 103 33 84 200 161 193 82
#> 19.34 22.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 80 80.1 185 35.1 44 11 141 109 152 173 198 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 165 151 71 33.1 53 193.1 48 38 31 82.1 38.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 35.2 95 3 119 156 27 87 9 44.1 121 162 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 53.1 28 191 172 84.1 20 64 67 84.2 143 109.2 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 7 38.2 198.1 182 182.1 182.2 152.1 147 138.1 162.1 3.2 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 172.1 17 98 112 44.2 176 137 47 64.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01700361 0.50580602 0.42047118
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73996586 0.01496762 -0.15741588
#> grade_iii, Cure model
#> 0.76963970
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 128 20.35 1 35 0 1
#> 183 9.24 1 67 1 0
#> 61 10.12 1 36 0 1
#> 36 21.19 1 48 0 1
#> 195 11.76 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 110 17.56 1 65 0 1
#> 123 13.00 1 44 1 0
#> 154 12.63 1 20 1 0
#> 99 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 154.1 12.63 1 20 1 0
#> 8 18.43 1 32 0 0
#> 180 14.82 1 37 0 0
#> 81 14.06 1 34 0 0
#> 127 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 127.1 3.53 1 62 0 1
#> 140 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 140.1 12.68 1 59 1 0
#> 192 16.44 1 31 1 0
#> 150 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 171 16.57 1 41 0 1
#> 55 19.34 1 69 0 1
#> 93 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 29 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 149 8.37 1 33 1 0
#> 61.1 10.12 1 36 0 1
#> 100.1 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 55.1 19.34 1 69 0 1
#> 42 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 45 17.42 1 54 0 1
#> 155 13.08 1 26 0 0
#> 157 15.10 1 47 0 0
#> 123.1 13.00 1 44 1 0
#> 188 16.16 1 46 0 1
#> 36.1 21.19 1 48 0 1
#> 99.1 21.19 1 38 0 1
#> 66 22.13 1 53 0 0
#> 130 16.47 1 53 0 1
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 55.2 19.34 1 69 0 1
#> 167.1 15.55 1 56 1 0
#> 171.1 16.57 1 41 0 1
#> 164 23.60 1 76 0 1
#> 50 10.02 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 4.1 17.64 1 NA 0 1
#> 61.2 10.12 1 36 0 1
#> 169 22.41 1 46 0 0
#> 92 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 93.1 10.33 1 52 0 1
#> 25.1 6.32 1 34 1 0
#> 110.1 17.56 1 65 0 1
#> 43 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 100.2 16.07 1 60 0 0
#> 68 20.62 1 44 0 0
#> 195.1 11.76 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 101 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 188.1 16.16 1 46 0 1
#> 129.1 23.41 1 53 1 0
#> 153.1 21.33 1 55 1 0
#> 49 12.19 1 48 1 0
#> 77 7.27 1 67 0 1
#> 179 18.63 1 42 0 0
#> 78 23.88 1 43 0 0
#> 130.1 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 154.2 12.63 1 20 1 0
#> 157.1 15.10 1 47 0 0
#> 153.2 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 184 17.77 1 38 0 0
#> 153.3 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 140.2 12.68 1 59 1 0
#> 150.1 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 90 20.94 1 50 0 1
#> 93.2 10.33 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 194 22.40 1 38 0 1
#> 117.1 17.46 1 26 0 1
#> 55.3 19.34 1 69 0 1
#> 91.1 5.33 1 61 0 1
#> 25.2 6.32 1 34 1 0
#> 16 8.71 1 71 0 1
#> 195.2 11.76 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 164.1 23.60 1 76 0 1
#> 166.1 19.98 1 48 0 0
#> 98 24.00 0 34 1 0
#> 148 24.00 0 61 1 0
#> 126 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 151 24.00 0 42 0 0
#> 98.1 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 17 24.00 0 38 0 1
#> 121.1 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 126.1 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 21.1 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 83 24.00 0 6 0 0
#> 72.1 24.00 0 40 0 1
#> 191 24.00 0 60 0 1
#> 87 24.00 0 27 0 0
#> 17.1 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 19.1 24.00 0 57 0 1
#> 1 24.00 0 23 1 0
#> 176.1 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 138.1 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 138.2 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 186 24.00 0 45 1 0
#> 1.2 24.00 0 23 1 0
#> 162 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 102 24.00 0 49 0 0
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 116 24.00 0 58 0 1
#> 103 24.00 0 56 1 0
#> 142.1 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 144.1 24.00 0 28 0 1
#> 126.2 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 71.1 24.00 0 51 0 0
#> 47.2 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 116.1 24.00 0 58 0 1
#> 54.1 24.00 0 53 1 0
#> 160.1 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 172.1 24.00 0 41 0 0
#> 156.2 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 161.1 24.00 0 45 0 0
#> 198.1 24.00 0 66 0 1
#> 65.1 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 72.2 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 1.3 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.740 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model -0.157 NA NA NA
#> 4 grade_iii, Cure model 0.770 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0170 NA NA NA
#> 2 grade_ii, Survival model 0.506 NA NA NA
#> 3 grade_iii, Survival model 0.420 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73997 0.01497 -0.15742 0.76964
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 252.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73996586 0.01496762 -0.15741588 0.76963970
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01700361 0.50580602 0.42047118
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 6.914696e-01 8.625296e-02 8.280727e-01 7.589801e-01 5.500210e-02
#> [6] 3.821503e-01 2.223637e-01 5.489128e-01 6.133054e-01 5.500210e-02
#> [11] 5.168291e-03 6.133054e-01 1.782050e-01 4.743117e-01 5.110716e-01
#> [16] 9.706340e-01 4.216138e-04 9.706340e-01 5.744395e-01 2.599274e-01
#> [21] 1.952306e-01 5.744395e-01 3.192172e-01 9.219185e-02 2.041567e-01
#> [26] 2.794415e-01 1.320307e-01 7.182897e-01 4.045850e-01 3.500043e-01
#> [31] 2.411296e-01 4.272143e-01 2.796657e-02 8.563743e-01 7.589801e-01
#> [36] 3.500043e-01 8.706027e-01 1.320307e-01 6.517333e-01 1.616481e-01
#> [41] 2.696152e-01 5.361271e-01 4.505362e-01 5.489128e-01 3.294584e-01
#> [46] 5.500210e-02 5.500210e-02 2.385814e-02 2.990769e-01 3.703243e-02
#> [51] 8.991796e-01 1.320307e-01 4.045850e-01 2.794415e-01 1.505934e-03
#> [56] 1.782050e-01 7.589801e-01 1.654051e-02 1.013739e-02 8.000550e-01
#> [61] 7.182897e-01 8.991796e-01 2.223637e-01 6.781210e-01 1.332899e-02
#> [66] 3.500043e-01 8.037902e-02 5.110716e-01 8.140981e-01 1.248490e-01
#> [71] 3.294584e-01 5.168291e-03 3.703243e-02 6.648922e-01 8.848320e-01
#> [76] 1.698236e-01 5.280525e-05 2.990769e-01 1.045475e-01 6.133054e-01
#> [81] 4.505362e-01 3.703243e-02 1.177761e-01 2.131677e-01 3.703243e-02
#> [86] 9.416792e-01 4.388320e-01 5.744395e-01 9.219185e-02 4.986571e-01
#> [91] 3.933376e-01 7.472289e-02 7.182897e-01 6.914696e-01 2.013144e-02
#> [96] 2.411296e-01 1.320307e-01 9.416792e-01 8.991796e-01 8.421587e-01
#> [101] 4.743117e-01 3.241451e-02 1.505934e-03 1.045475e-01 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00
#>
#> $Time
#> 52 128 183 61 36 6 110 123 154 99 129 154.1 8
#> 10.42 20.35 9.24 10.12 21.19 15.64 17.56 13.00 12.63 21.19 23.41 12.63 18.43
#> 180 81 127 168 127.1 140 111 88 140.1 192 150 108 171
#> 14.82 14.06 3.53 23.72 3.53 12.68 17.45 18.37 12.68 16.44 20.33 18.29 16.57
#> 55 93 167 100 117 29 175 149 61.1 100.1 70 55.1 42
#> 19.34 10.33 15.55 16.07 17.46 15.45 21.91 8.37 10.12 16.07 7.38 19.34 12.43
#> 97 45 155 157 123.1 188 36.1 99.1 66 130 153 25 55.2
#> 19.14 17.42 13.08 15.10 13.00 16.16 21.19 21.19 22.13 16.47 21.33 6.32 19.34
#> 167.1 171.1 164 8.1 61.2 169 92 145 93.1 25.1 110.1 43 63
#> 15.55 16.57 23.60 18.43 10.12 22.41 22.92 10.07 10.33 6.32 17.56 12.10 22.77
#> 100.2 68 81.1 101 170 188.1 129.1 153.1 49 77 179 78 130.1
#> 16.07 20.62 14.06 9.97 19.54 16.16 23.41 21.33 12.19 7.27 18.63 23.88 16.47
#> 166 154.2 157.1 153.2 105 184 153.3 91 18 140.2 150.1 57 39
#> 19.98 12.63 15.10 21.33 19.75 17.77 21.33 5.33 15.21 12.68 20.33 14.46 15.59
#> 90 93.2 52.1 194 117.1 55.3 91.1 25.2 16 180.1 136 164.1 166.1
#> 20.94 10.33 10.42 22.40 17.46 19.34 5.33 6.32 8.71 14.82 21.83 23.60 19.98
#> 98 148 126 65 28 196 64 95 121 74 151 98.1 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 121.1 118 131 72 126.1 21 176 94 178 71 144 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 142 173 138 104 21.1 146 47.1 3 75 83 72.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 17.1 141 19 19.1 1 176.1 2 138.1 1.1 138.2 54 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.2 162 33.1 161 102 160 156 141.1 135 116 103 142.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 144.1 126.2 198 71.1 47.2 132 112 116.1 54.1 160.1 156.1 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 82 161.1 198.1 65.1 62 72.2 119 1.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006891884 0.608821551 0.368767254
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.57361881 0.01518465 -0.06240258
#> grade_iii, Cure model
#> 0.33216619
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 91 5.33 1 61 0 1
#> 32 20.90 1 37 1 0
#> 37.1 12.52 1 57 1 0
#> 158 20.14 1 74 1 0
#> 110 17.56 1 65 0 1
#> 133 14.65 1 57 0 0
#> 128 20.35 1 35 0 1
#> 168 23.72 1 70 0 0
#> 6 15.64 1 39 0 0
#> 77 7.27 1 67 0 1
#> 90 20.94 1 50 0 1
#> 134 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 90.1 20.94 1 50 0 1
#> 101 9.97 1 10 0 1
#> 60 13.15 1 38 1 0
#> 15 22.68 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 37.2 12.52 1 57 1 0
#> 70 7.38 1 30 1 0
#> 6.1 15.64 1 39 0 0
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 49 12.19 1 48 1 0
#> 106 16.67 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 40 18.00 1 28 1 0
#> 97 19.14 1 65 0 1
#> 14 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 13 14.34 1 54 0 1
#> 69 23.23 1 25 0 1
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 30 17.43 1 78 0 0
#> 50 10.02 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 79 16.23 1 54 1 0
#> 177.2 12.53 1 75 0 0
#> 5 16.43 1 51 0 1
#> 50.1 10.02 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 101.1 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 123 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 100 16.07 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 157 15.10 1 47 0 0
#> 8 18.43 1 32 0 0
#> 195 11.76 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 60.1 13.15 1 38 1 0
#> 158.1 20.14 1 74 1 0
#> 169 22.41 1 46 0 0
#> 58 19.34 1 39 0 0
#> 5.1 16.43 1 51 0 1
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 145.1 10.07 1 65 1 0
#> 113 22.86 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 40.1 18.00 1 28 1 0
#> 108 18.29 1 39 0 1
#> 23.1 16.92 1 61 0 0
#> 23.2 16.92 1 61 0 0
#> 88 18.37 1 47 0 0
#> 42 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 155 13.08 1 26 0 0
#> 167 15.55 1 56 1 0
#> 188.2 16.16 1 46 0 1
#> 63 22.77 1 31 1 0
#> 18.1 15.21 1 49 1 0
#> 79.2 16.23 1 54 1 0
#> 145.2 10.07 1 65 1 0
#> 50.2 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 180 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 157.1 15.10 1 47 0 0
#> 10 10.53 1 34 0 0
#> 30.2 17.43 1 78 0 0
#> 168.2 23.72 1 70 0 0
#> 85.1 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 26 15.77 1 49 0 1
#> 68.1 20.62 1 44 0 0
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 171 16.57 1 41 0 1
#> 158.2 20.14 1 74 1 0
#> 79.3 16.23 1 54 1 0
#> 25 6.32 1 34 1 0
#> 154 12.63 1 20 1 0
#> 81 14.06 1 34 0 0
#> 169.1 22.41 1 46 0 0
#> 70.1 7.38 1 30 1 0
#> 30.3 17.43 1 78 0 0
#> 81.1 14.06 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 168.3 23.72 1 70 0 0
#> 80 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 156 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 156.1 24.00 0 50 1 0
#> 35.2 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 186 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 67.2 24.00 0 25 0 0
#> 176 24.00 0 43 0 1
#> 141.1 24.00 0 44 1 0
#> 67.3 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 67.4 24.00 0 25 0 0
#> 115 24.00 0 NA 1 0
#> 182 24.00 0 35 0 0
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 46 24.00 0 71 0 0
#> 17.1 24.00 0 38 0 1
#> 148.1 24.00 0 61 1 0
#> 75 24.00 0 21 1 0
#> 156.2 24.00 0 50 1 0
#> 141.2 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 67.5 24.00 0 25 0 0
#> 178 24.00 0 52 1 0
#> 182.1 24.00 0 35 0 0
#> 71.1 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 28.1 24.00 0 67 1 0
#> 186.1 24.00 0 45 1 0
#> 67.6 24.00 0 25 0 0
#> 65.1 24.00 0 57 1 0
#> 120 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 21.1 24.00 0 47 0 0
#> 2.1 24.00 0 9 0 0
#> 53.1 24.00 0 32 0 1
#> 138.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 80.2 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 191.1 24.00 0 60 0 1
#> 174.1 24.00 0 49 1 0
#> 95.1 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 137 24.00 0 45 1 0
#> 176.1 24.00 0 43 0 1
#> 65.2 24.00 0 57 1 0
#> 121.1 24.00 0 57 1 0
#> 75.1 24.00 0 21 1 0
#> 118 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.574 NA NA NA
#> 2 age, Cure model 0.0152 NA NA NA
#> 3 grade_ii, Cure model -0.0624 NA NA NA
#> 4 grade_iii, Cure model 0.332 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00689 NA NA NA
#> 2 grade_ii, Survival model 0.609 NA NA NA
#> 3 grade_iii, Survival model 0.369 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57362 0.01518 -0.06240 0.33217
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.1
#> Residual Deviance: 264.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57361881 0.01518465 -0.06240258 0.33216619
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006891884 0.608821551 0.368767254
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.798546957 0.981986446 0.146334451 0.798546957 0.192608690 0.321916192
#> [7] 0.658090067 0.183251763 0.006125773 0.574045548 0.963947877 0.127680699
#> [13] 0.312834533 0.667539448 0.127680699 0.900265335 0.714531911 0.060031671
#> [19] 0.006125773 0.798546957 0.945970973 0.574045548 0.770579258 0.508938066
#> [25] 0.155716966 0.592787387 0.164891711 0.835627226 0.396050635 0.396050635
#> [31] 0.294764536 0.237644819 0.751910956 0.872791044 0.676968570 0.030954372
#> [37] 0.555446867 0.367553680 0.331017419 0.770579258 0.472310686 0.770579258
#> [43] 0.453225116 0.676968570 0.117952271 0.918545284 0.434125647 0.900265335
#> [49] 0.089153433 0.936853249 0.742558086 0.089153433 0.536583868 0.331017419
#> [55] 0.630070228 0.247058438 0.472310686 0.714531911 0.192608690 0.069725489
#> [61] 0.228259556 0.453225116 0.285282382 0.275674010 0.872791044 0.040601086
#> [67] 0.555446867 0.611606850 0.508938066 0.294764536 0.266126870 0.367553680
#> [73] 0.367553680 0.256543621 0.826280609 0.854275184 0.733162924 0.602215471
#> [79] 0.508938066 0.050761714 0.611606850 0.472310686 0.872791044 0.218964410
#> [85] 0.648684559 0.927694137 0.630070228 0.844940458 0.331017419 0.006125773
#> [91] 0.434125647 0.108133010 0.546017935 0.164891711 0.990990896 0.424562054
#> [97] 0.414997716 0.192608690 0.472310686 0.972986150 0.761279529 0.695697269
#> [103] 0.069725489 0.945970973 0.331017419 0.695697269 0.854275184 0.006125773
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 37 91 32 37.1 158 110 133 128 168 6 77 90 134
#> 12.52 5.33 20.90 12.52 20.14 17.56 14.65 20.35 23.72 15.64 7.27 20.94 17.81
#> 96 90.1 101 60 15 168.1 37.2 70 6.1 177 188 190 39
#> 14.54 20.94 9.97 13.15 22.68 23.72 12.52 7.38 15.64 12.53 16.16 20.81 15.59
#> 68 49 106 106.1 40 97 14 145 13 69 125 23 30
#> 20.62 12.19 16.67 16.67 18.00 19.14 12.89 10.07 14.34 23.23 15.65 16.92 17.43
#> 177.1 79 177.2 5 13.1 99 187 85 101.1 194 149 123 194.1
#> 12.53 16.23 12.53 16.43 14.34 21.19 9.92 16.44 9.97 22.40 8.37 13.00 22.40
#> 100 30.1 157 8 79.1 60.1 158.1 169 58 5.1 41 51 145.1
#> 16.07 17.43 15.10 18.43 16.23 13.15 20.14 22.41 19.34 16.43 18.02 18.23 10.07
#> 113 125.1 18 188.1 40.1 108 23.1 23.2 88 42 61 155 167
#> 22.86 15.65 15.21 16.16 18.00 18.29 16.92 16.92 18.37 12.43 10.12 13.08 15.55
#> 188.2 63 18.1 79.2 145.2 105 180 16 157.1 10 30.2 168.2 85.1
#> 16.16 22.77 15.21 16.23 10.07 19.75 14.82 8.71 15.10 10.53 17.43 23.72 16.44
#> 197 26 68.1 127 130 171 158.2 79.3 25 154 81 169.1 70.1
#> 21.60 15.77 20.62 3.53 16.47 16.57 20.14 16.23 6.32 12.63 14.06 22.41 7.38
#> 30.3 81.1 61.1 168.3 80 193 47 21 191 35 19 135 28
#> 17.43 14.06 10.12 23.72 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 53 9 35.1 67.1 156 103 147 156.1 35.2 142 132 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 65 109 141 20 148 152 121 48 135.1 67.2 176 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.3 2 17 44 67.4 182 12 174 46 17.1 148.1 75 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 162 138 72 67.5 178 182.1 71.1 80.1 165 28.1 186.1 67.6
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 120 112 94 198 196 21.1 2.1 53.1 138.1 74 64 80.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 191.1 174.1 95.1 200 137 176.1 65.2 121.1 75.1 118 138.2 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003074817 0.883949755 0.575888582
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.028121948 -0.003738249 0.414524911
#> grade_iii, Cure model
#> 0.742302893
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 88 18.37 1 47 0 0
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 79 16.23 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 70 7.38 1 30 1 0
#> 149 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 113 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 49 12.19 1 48 1 0
#> 61 10.12 1 36 0 1
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 63 22.77 1 31 1 0
#> 25 6.32 1 34 1 0
#> 43 12.10 1 61 0 1
#> 49.1 12.19 1 48 1 0
#> 61.1 10.12 1 36 0 1
#> 61.2 10.12 1 36 0 1
#> 79.1 16.23 1 54 1 0
#> 106.1 16.67 1 49 1 0
#> 150 20.33 1 48 0 0
#> 110 17.56 1 65 0 1
#> 89.1 11.44 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 181 16.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 60.2 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 26 15.77 1 49 0 1
#> 24.1 23.89 1 38 0 0
#> 70.1 7.38 1 30 1 0
#> 40 18.00 1 28 1 0
#> 55.1 19.34 1 69 0 1
#> 5 16.43 1 51 0 1
#> 111.1 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 125 15.65 1 67 1 0
#> 179 18.63 1 42 0 0
#> 107.1 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 88.1 18.37 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 90 20.94 1 50 0 1
#> 164 23.60 1 76 0 1
#> 89.2 11.44 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 175 21.91 1 43 0 0
#> 157 15.10 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 92 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 125.1 15.65 1 67 1 0
#> 154.1 12.63 1 20 1 0
#> 24.2 23.89 1 38 0 0
#> 81 14.06 1 34 0 0
#> 40.1 18.00 1 28 1 0
#> 199 19.81 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 37 12.52 1 57 1 0
#> 166 19.98 1 48 0 0
#> 177.1 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 30.1 17.43 1 78 0 0
#> 188.1 16.16 1 46 0 1
#> 105 19.75 1 60 0 0
#> 70.2 7.38 1 30 1 0
#> 183 9.24 1 67 1 0
#> 171 16.57 1 41 0 1
#> 4 17.64 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 106.2 16.67 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 181.1 16.46 1 45 0 1
#> 32.1 20.90 1 37 1 0
#> 101.1 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 181.2 16.46 1 45 0 1
#> 15 22.68 1 48 0 0
#> 18 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 25.2 6.32 1 34 1 0
#> 171.1 16.57 1 41 0 1
#> 15.1 22.68 1 48 0 0
#> 78 23.88 1 43 0 0
#> 110.1 17.56 1 65 0 1
#> 63.1 22.77 1 31 1 0
#> 37.1 12.52 1 57 1 0
#> 184.1 17.77 1 38 0 0
#> 180 14.82 1 37 0 0
#> 189 10.51 1 NA 1 0
#> 60.3 13.15 1 38 1 0
#> 96.1 14.54 1 33 0 1
#> 199.1 19.81 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 122 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 102 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 135 24.00 0 58 1 0
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 28 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 143 24.00 0 51 0 0
#> 122.1 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 67 24.00 0 25 0 0
#> 191.1 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 12.2 24.00 0 63 0 0
#> 7.1 24.00 0 37 1 0
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 126.1 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 1 24.00 0 23 1 0
#> 84 24.00 0 39 0 1
#> 33 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 172.2 24.00 0 41 0 0
#> 138.1 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 1.1 24.00 0 23 1 0
#> 173.1 24.00 0 19 0 1
#> 163.1 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 138.2 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 156.1 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 138.3 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 178.2 24.00 0 52 1 0
#> 186.1 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 102.2 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 31.2 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 109.1 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 102.3 24.00 0 49 0 0
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 104 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 146.1 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0281 NA NA NA
#> 2 age, Cure model -0.00374 NA NA NA
#> 3 grade_ii, Cure model 0.415 NA NA NA
#> 4 grade_iii, Cure model 0.742 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00307 NA NA NA
#> 2 grade_ii, Survival model 0.884 NA NA NA
#> 3 grade_iii, Survival model 0.576 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.028122 -0.003738 0.414525 0.742303
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 259.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.028121948 -0.003738249 0.414524911 0.742302893
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003074817 0.883949755 0.575888582
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.32994917 0.62989134 0.51343011 0.50353017 0.31434542 0.97117068
#> [7] 0.58728161 0.99524186 0.80611239 0.84191940 0.42138108 0.70580796
#> [13] 0.95635053 0.95125339 0.60438979 0.47391524 0.87087841 0.23205801
#> [19] 0.73377785 0.87658585 0.92008419 0.76079484 0.05348635 0.25249740
#> [25] 0.98095773 0.88770306 0.87658585 0.92008419 0.92008419 0.70580796
#> [31] 0.62989134 0.44234100 0.56963090 0.93574013 0.66880548 0.89323934
#> [37] 0.38615610 0.62136775 0.80611239 0.80611239 0.69097282 0.74071872
#> [43] 0.05348635 0.95635053 0.53292345 0.47391524 0.69843295 0.58728161
#> [49] 0.90943778 0.74759082 0.49361007 0.89323934 0.18841564 0.51343011
#> [55] 0.78695914 0.35965872 0.40976585 0.16250754 0.97117068 0.34484912
#> [61] 0.77393985 0.98095773 0.21141962 0.83010555 0.74759082 0.83010555
#> [67] 0.05348635 0.79971464 0.53292345 0.55131501 0.85369042 0.45290786
#> [73] 0.84191940 0.71993536 0.60438979 0.71993536 0.46343566 0.95635053
#> [79] 0.94610998 0.65340941 0.37334561 0.62989134 0.90943778 0.38615610
#> [85] 0.66880548 0.42138108 0.93574013 0.86516339 0.66880548 0.28368750
#> [91] 0.76741840 0.90402988 0.98095773 0.65340941 0.28368750 0.13021037
#> [97] 0.56963090 0.25249740 0.85369042 0.55131501 0.78045277 0.80611239
#> [103] 0.78695914 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 194 106 88 8 169 77 111 91 60 177 32 79 70
#> 22.40 16.67 18.37 18.43 22.41 7.27 17.45 5.33 13.15 12.53 20.90 16.23 7.38
#> 149 30 55 56 113 100 49 61 6 24 63 25 43
#> 8.37 17.43 19.34 12.21 22.86 16.07 12.19 10.12 15.64 23.89 22.77 6.32 12.10
#> 49.1 61.1 61.2 79.1 106.1 150 110 101 181 107 99 23 60.1
#> 12.19 10.12 10.12 16.23 16.67 20.33 17.56 9.97 16.46 11.18 21.19 16.92 13.15
#> 60.2 85 26 24.1 70.1 40 55.1 5 111.1 93 125 179 107.1
#> 13.15 16.44 15.77 23.89 7.38 18.00 19.34 16.43 17.45 10.33 15.65 18.63 11.18
#> 69 88.1 96 197 90 164 77.1 175 157 25.1 92 154 125.1
#> 23.23 18.37 14.54 21.60 20.94 23.60 7.27 21.91 15.10 6.32 22.92 12.63 15.65
#> 154.1 24.2 81 40.1 184 37 166 177.1 188 30.1 188.1 105 70.2
#> 12.63 23.89 14.06 18.00 17.77 12.52 19.98 12.53 16.16 17.43 16.16 19.75 7.38
#> 183 171 153 106.2 93.1 36 181.1 32.1 101.1 42 181.2 15 18
#> 9.24 16.57 21.33 16.67 10.33 21.19 16.46 20.90 9.97 12.43 16.46 22.68 15.21
#> 10 25.2 171.1 15.1 78 110.1 63.1 37.1 184.1 180 60.3 96.1 122
#> 10.53 6.32 16.57 22.68 23.88 17.56 22.77 12.52 17.77 14.82 13.15 14.54 24.00
#> 53 87 35 196 102 191 138 174 135 186 163 27 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 103 172 7 28 193 126 120 94 143 122.1 178 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 198 67 191.1 19 151 74 12.1 146 12.2 7.1 22 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 172.1 126.1 54 1 84 33 173 172.2 138.1 160 46 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 82 1.1 173.1 163.1 74.1 21 176 143.1 138.2 62 119 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 118 138.3 121 178.2 186.1 109 102.2 47 80 31.2 196.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 2 102.3 83 11 104 95.1 146.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01120263 0.57641842 0.27353317
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9482302 0.0187761 -0.1190052
#> grade_iii, Cure model
#> 1.0454475
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 129 23.41 1 53 1 0
#> 42 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 51 18.23 1 83 0 1
#> 91 5.33 1 61 0 1
#> 30 17.43 1 78 0 0
#> 189 10.51 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 140 12.68 1 59 1 0
#> 25 6.32 1 34 1 0
#> 177 12.53 1 75 0 0
#> 43 12.10 1 61 0 1
#> 41 18.02 1 40 1 0
#> 36 21.19 1 48 0 1
#> 127 3.53 1 62 0 1
#> 18 15.21 1 49 1 0
#> 175 21.91 1 43 0 0
#> 175.1 21.91 1 43 0 0
#> 128 20.35 1 35 0 1
#> 93 10.33 1 52 0 1
#> 181.1 16.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 90 20.94 1 50 0 1
#> 139 21.49 1 63 1 0
#> 86 23.81 1 58 0 1
#> 77 7.27 1 67 0 1
#> 51.1 18.23 1 83 0 1
#> 179 18.63 1 42 0 0
#> 181.2 16.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 70 7.38 1 30 1 0
#> 179.1 18.63 1 42 0 0
#> 92 22.92 1 47 0 1
#> 26 15.77 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 18.1 15.21 1 49 1 0
#> 8 18.43 1 32 0 0
#> 42.1 12.43 1 49 0 1
#> 81 14.06 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 157 15.10 1 47 0 0
#> 59 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 153 21.33 1 55 1 0
#> 168 23.72 1 70 0 0
#> 56.1 12.21 1 60 0 0
#> 168.1 23.72 1 70 0 0
#> 13.1 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 85 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 177.1 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 32 20.90 1 37 1 0
#> 25.1 6.32 1 34 1 0
#> 10 10.53 1 34 0 0
#> 43.1 12.10 1 61 0 1
#> 78 23.88 1 43 0 0
#> 136 21.83 1 43 0 1
#> 155 13.08 1 26 0 0
#> 40 18.00 1 28 1 0
#> 168.2 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 88 18.37 1 47 0 0
#> 128.1 20.35 1 35 0 1
#> 195.1 11.76 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 30.1 17.43 1 78 0 0
#> 85.1 16.44 1 36 0 0
#> 99 21.19 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 92.1 22.92 1 47 0 1
#> 66.1 22.13 1 53 0 0
#> 158.1 20.14 1 74 1 0
#> 168.3 23.72 1 70 0 0
#> 134 17.81 1 47 1 0
#> 164 23.60 1 76 0 1
#> 155.1 13.08 1 26 0 0
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 192 16.44 1 31 1 0
#> 106.1 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 37 12.52 1 57 1 0
#> 70.1 7.38 1 30 1 0
#> 99.1 21.19 1 38 0 1
#> 41.1 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 136.1 21.83 1 43 0 1
#> 197.1 21.60 1 69 1 0
#> 85.2 16.44 1 36 0 0
#> 88.1 18.37 1 47 0 0
#> 18.2 15.21 1 49 1 0
#> 139.1 21.49 1 63 1 0
#> 23 16.92 1 61 0 0
#> 145.2 10.07 1 65 1 0
#> 55 19.34 1 69 0 1
#> 99.2 21.19 1 38 0 1
#> 43.2 12.10 1 61 0 1
#> 41.2 18.02 1 40 1 0
#> 4.1 17.64 1 NA 0 1
#> 92.2 22.92 1 47 0 1
#> 161 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 1 24.00 0 23 1 0
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 162 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 115 24.00 0 NA 1 0
#> 44 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 161.1 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 182.1 24.00 0 35 0 0
#> 151 24.00 0 42 0 0
#> 163.1 24.00 0 66 0 0
#> 20.1 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 20.2 24.00 0 46 1 0
#> 137.1 24.00 0 45 1 0
#> 2.1 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 173 24.00 0 19 0 1
#> 46.1 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 28 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 191 24.00 0 60 0 1
#> 156 24.00 0 50 1 0
#> 142.1 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 148 24.00 0 61 1 0
#> 103 24.00 0 56 1 0
#> 103.1 24.00 0 56 1 0
#> 80.1 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 83.1 24.00 0 6 0 0
#> 3.1 24.00 0 31 1 0
#> 161.2 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 75.1 24.00 0 21 1 0
#> 72.1 24.00 0 40 0 1
#> 28.1 24.00 0 67 1 0
#> 46.2 24.00 0 71 0 0
#> 142.2 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 67.2 24.00 0 25 0 0
#> 162.1 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 95.1 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.948 NA NA NA
#> 2 age, Cure model 0.0188 NA NA NA
#> 3 grade_ii, Cure model -0.119 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0112 NA NA NA
#> 2 grade_ii, Survival model 0.576 NA NA NA
#> 3 grade_iii, Survival model 0.274 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94823 0.01878 -0.11901 1.04545
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 250 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9482302 0.0187761 -0.1190052 1.0454475
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01120263 0.57641842 0.27353317
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2563073477 0.1862567633 0.8666499755 0.0298696101 0.7598827683
#> [6] 0.7831341452 0.3326606998 0.9755602330 0.4129010575 0.8788277089
#> [11] 0.5374031740 0.4645714079 0.6127869740 0.7137822531 0.9514256282
#> [16] 0.7251959879 0.8067283776 0.3529794757 0.1374555766 0.9877541416
#> [21] 0.5697972364 0.0669961658 0.0669961658 0.2034382836 0.8544930329
#> [26] 0.4645714079 0.0004873148 0.1690623971 0.1130226129 0.0049459820
#> [31] 0.9392135015 0.3326606998 0.2840994869 0.4645714079 0.6910229937
#> [36] 0.9150663759 0.2840994869 0.0360371774 0.5588950140 0.5374031740
#> [41] 0.5697972364 0.3031489822 0.7598827683 0.6571744172 0.8788277089
#> [46] 0.6018323152 0.6349226900 0.1291186694 0.0082435754 0.7831341452
#> [51] 0.0082435754 0.6349226900 0.2746515943 0.4956999359 0.7023832974
#> [56] 0.7251959879 0.6238084937 0.1776960865 0.9514256282 0.8423818951
#> [61] 0.8067283776 0.0022519945 0.0818345863 0.6684571167 0.3826705561
#> [66] 0.0082435754 0.0533225528 0.3129222844 0.2034382836 0.4438695369
#> [71] 0.4129010575 0.4956999359 0.1374555766 0.2563073477 0.2294378660
#> [76] 0.0360371774 0.0533225528 0.2294378660 0.0082435754 0.3927547190
#> [81] 0.0237282952 0.6684571167 0.2205585722 0.1947737829 0.4956999359
#> [86] 0.4438695369 0.0972032129 0.7482531154 0.9150663759 0.1374555766
#> [91] 0.3529794757 0.4028256678 0.0818345863 0.0972032129 0.4956999359
#> [96] 0.3129222844 0.5697972364 0.1130226129 0.4333813054 0.8788277089
#> [101] 0.2471534662 0.1374555766 0.8067283776 0.3529794757 0.0360371774
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000
#>
#> $Time
#> 76 190 61 129 42 56 51 91 30 145 5 181 180
#> 19.22 20.81 10.12 23.41 12.43 12.21 18.23 5.33 17.43 10.07 16.43 16.46 14.82
#> 140 25 177 43 41 36 127 18 175 175.1 128 93 181.1
#> 12.68 6.32 12.53 12.10 18.02 21.19 3.53 15.21 21.91 21.91 20.35 10.33 16.46
#> 24 90 139 86 77 51.1 179 181.2 123 70 179.1 92 26
#> 23.89 20.94 21.49 23.81 7.27 18.23 18.63 16.46 13.00 7.38 18.63 22.92 15.77
#> 5.1 18.1 8 42.1 81 145.1 157 13 153 168 56.1 168.1 13.1
#> 16.43 15.21 18.43 12.43 14.06 10.07 15.10 14.34 21.33 23.72 12.21 23.72 14.34
#> 97 85 14 177.1 133 32 25.1 10 43.1 78 136 155 40
#> 19.14 16.44 12.89 12.53 14.65 20.90 6.32 10.53 12.10 23.88 21.83 13.08 18.00
#> 168.2 66 88 128.1 106 30.1 85.1 99 76.1 158 92.1 66.1 158.1
#> 23.72 22.13 18.37 20.35 16.67 17.43 16.44 21.19 19.22 20.14 22.92 22.13 20.14
#> 168.3 134 164 155.1 150 68 192 106.1 197 37 70.1 99.1 41.1
#> 23.72 17.81 23.60 13.08 20.33 20.62 16.44 16.67 21.60 12.52 7.38 21.19 18.02
#> 117 136.1 197.1 85.2 88.1 18.2 139.1 23 145.2 55 99.2 43.2 41.2
#> 17.46 21.83 21.60 16.44 18.37 15.21 21.49 16.92 10.07 19.34 21.19 12.10 18.02
#> 92.2 161 104 67 137 22 94 80 185 163 200 3 20
#> 22.92 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 2 1 165 71 27 67.1 138 185.1 83 162 87 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 95 33 46 135 161.1 38 31 17 146 182.1 151 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 174 142 193 176 21 122 75 20.2 137.1 2.1 141 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 46.1 144 28 12 72 191 156 142.1 135.1 148 103 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 19 83.1 3.1 161.2 65 122.1 75.1 72.1 28.1 46.2 142.2 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 143 156.1 143.1 67.2 162.1 186 95.1 31.1 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01198009 0.45612710 0.41360515
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.20330661 0.02347921 0.09453753
#> grade_iii, Cure model
#> 0.81562802
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 136 21.83 1 43 0 1
#> 55 19.34 1 69 0 1
#> 85 16.44 1 36 0 0
#> 91 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 18 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 140 12.68 1 59 1 0
#> 133 14.65 1 57 0 0
#> 58 19.34 1 39 0 0
#> 42 12.43 1 49 0 1
#> 192 16.44 1 31 1 0
#> 106 16.67 1 49 1 0
#> 134 17.81 1 47 1 0
#> 93 10.33 1 52 0 1
#> 70 7.38 1 30 1 0
#> 26 15.77 1 49 0 1
#> 16 8.71 1 71 0 1
#> 107 11.18 1 54 1 0
#> 105 19.75 1 60 0 0
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 63 22.77 1 31 1 0
#> 100 16.07 1 60 0 0
#> 18.1 15.21 1 49 1 0
#> 41 18.02 1 40 1 0
#> 14 12.89 1 21 0 0
#> 18.2 15.21 1 49 1 0
#> 66 22.13 1 53 0 0
#> 61 10.12 1 36 0 1
#> 195 11.76 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 41.1 18.02 1 40 1 0
#> 66.1 22.13 1 53 0 0
#> 78 23.88 1 43 0 0
#> 166 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 188 16.16 1 46 0 1
#> 100.1 16.07 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 157.1 15.10 1 47 0 0
#> 170 19.54 1 43 0 1
#> 184 17.77 1 38 0 0
#> 166.1 19.98 1 48 0 0
#> 23 16.92 1 61 0 0
#> 69 23.23 1 25 0 1
#> 105.1 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 16.1 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 123 13.00 1 44 1 0
#> 70.1 7.38 1 30 1 0
#> 157.2 15.10 1 47 0 0
#> 111.2 17.45 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 93.1 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 188.1 16.16 1 46 0 1
#> 68 20.62 1 44 0 0
#> 6 15.64 1 39 0 0
#> 52 10.42 1 52 0 1
#> 8 18.43 1 32 0 0
#> 140.1 12.68 1 59 1 0
#> 79 16.23 1 54 1 0
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 86 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 140.2 12.68 1 59 1 0
#> 139 21.49 1 63 1 0
#> 61.1 10.12 1 36 0 1
#> 50 10.02 1 NA 1 0
#> 18.3 15.21 1 49 1 0
#> 91.1 5.33 1 61 0 1
#> 107.1 11.18 1 54 1 0
#> 107.2 11.18 1 54 1 0
#> 93.2 10.33 1 52 0 1
#> 93.3 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 42.1 12.43 1 49 0 1
#> 68.1 20.62 1 44 0 0
#> 110 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 170.1 19.54 1 43 0 1
#> 36 21.19 1 48 0 1
#> 51 18.23 1 83 0 1
#> 181 16.46 1 45 0 1
#> 157.3 15.10 1 47 0 0
#> 155 13.08 1 26 0 0
#> 171.1 16.57 1 41 0 1
#> 66.2 22.13 1 53 0 0
#> 13 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 42.2 12.43 1 49 0 1
#> 45 17.42 1 54 0 1
#> 177.1 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 52.1 10.42 1 52 0 1
#> 91.2 5.33 1 61 0 1
#> 170.2 19.54 1 43 0 1
#> 96 14.54 1 33 0 1
#> 60 13.15 1 38 1 0
#> 6.1 15.64 1 39 0 0
#> 74 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 54 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 112 24.00 0 61 0 0
#> 28 24.00 0 67 1 0
#> 72 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 182 24.00 0 35 0 0
#> 176 24.00 0 43 0 1
#> 54.1 24.00 0 53 1 0
#> 151 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 176.1 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 116 24.00 0 58 0 1
#> 151.1 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 161.1 24.00 0 45 0 0
#> 122 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 152.1 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 174 24.00 0 49 1 0
#> 151.2 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 80.1 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 21.1 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 119.1 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 147 24.00 0 76 1 0
#> 1 24.00 0 23 1 0
#> 160.1 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 176.2 24.00 0 43 0 1
#> 21.2 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 137.2 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 72.1 24.00 0 40 0 1
#> 173 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 178.1 24.00 0 52 1 0
#> 148.1 24.00 0 61 1 0
#> 94 24.00 0 51 0 1
#> 62.1 24.00 0 71 0 0
#> 31.1 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 182.1 24.00 0 35 0 0
#> 80.2 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 165 24.00 0 47 0 0
#> 122.1 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 87.1 24.00 0 27 0 0
#> 82.1 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 46.1 24.00 0 71 0 0
#> 160.2 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 120.1 24.00 0 68 0 1
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.20 NA NA NA
#> 2 age, Cure model 0.0235 NA NA NA
#> 3 grade_ii, Cure model 0.0945 NA NA NA
#> 4 grade_iii, Cure model 0.816 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0120 NA NA NA
#> 2 grade_ii, Survival model 0.456 NA NA NA
#> 3 grade_iii, Survival model 0.414 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.20331 0.02348 0.09454 0.81563
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.5
#> Residual Deviance: 258 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.20330661 0.02347921 0.09453753 0.81562802
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01198009 0.45612710 0.41360515
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.80032795 0.38785927 0.54889611 0.70817295 0.98503221 0.88489832
#> [7] 0.77924663 0.64760011 0.86134105 0.82099769 0.54889611 0.89404292
#> [13] 0.70817295 0.68213779 0.62487050 0.93733399 0.97733748 0.75649342
#> [19] 0.96563012 0.90737382 0.50031427 0.32017983 0.22654480 0.54889611
#> [25] 0.82099769 0.25575094 0.74485701 0.77924663 0.60926786 0.85639866
#> [31] 0.77924663 0.33964827 0.95357112 0.87554852 0.60926786 0.33964827
#> [37] 0.08688969 0.47882444 0.96163302 0.73302617 0.74485701 0.92462258
#> [43] 0.80032795 0.52087531 0.63255026 0.47882444 0.67532787 0.19532400
#> [49] 0.50031427 0.64760011 0.92032173 0.96563012 0.57527993 0.88489832
#> [55] 0.85144809 0.97733748 0.80032795 0.64760011 0.25575094 0.93733399
#> [61] 0.46755881 0.73302617 0.44369201 0.76225763 0.92891339 0.59255281
#> [67] 0.86134105 0.72692616 0.77364032 0.58395813 0.15791452 0.72072132
#> [73] 0.86134105 0.41789299 0.95357112 0.77924663 0.98503221 0.90737382
#> [79] 0.90737382 0.93733399 0.93733399 0.29892342 0.89404292 0.44369201
#> [85] 0.64017665 0.68882500 0.52087531 0.43111793 0.60108964 0.70176657
#> [91] 0.80032795 0.84644889 0.68882500 0.33964827 0.83638409 0.99627042
#> [97] 0.89404292 0.66844320 0.87554852 0.97344380 0.40360249 0.92891339
#> [103] 0.98503221 0.52087531 0.83127096 0.84143888 0.76225763 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 157 136 55 85 91 37 18 111 140 133 58 42 192
#> 15.10 21.83 19.34 16.44 5.33 12.52 15.21 17.45 12.68 14.65 19.34 12.43 16.44
#> 106 134 93 70 26 16 107 105 194 113 58.1 133.1 63
#> 16.67 17.81 10.33 7.38 15.77 8.71 11.18 19.75 22.40 22.86 19.34 14.65 22.77
#> 100 18.1 41 14 18.2 66 61 177 41.1 66.1 78 166 183
#> 16.07 15.21 18.02 12.89 15.21 22.13 10.12 12.53 18.02 22.13 23.88 19.98 9.24
#> 188 100.1 10 157.1 170 184 166.1 23 69 105.1 111.1 159 16.1
#> 16.16 16.07 10.53 15.10 19.54 17.77 19.98 16.92 23.23 19.75 17.45 10.55 8.71
#> 76 37.1 123 70.1 157.2 111.2 63.1 93.1 158 188.1 68 6 52
#> 19.22 12.52 13.00 7.38 15.10 17.45 22.77 10.33 20.14 16.16 20.62 15.64 10.42
#> 8 140.1 79 29 179 86 5 140.2 139 61.1 18.3 91.1 107.1
#> 18.43 12.68 16.23 15.45 18.63 23.81 16.43 12.68 21.49 10.12 15.21 5.33 11.18
#> 107.2 93.2 93.3 169 42.1 68.1 110 171 170.1 36 51 181 157.3
#> 11.18 10.33 10.33 22.41 12.43 20.62 17.56 16.57 19.54 21.19 18.23 16.46 15.10
#> 155 171.1 66.2 13 127 42.2 45 177.1 149 197 52.1 91.2 170.2
#> 13.08 16.57 22.13 14.34 3.53 12.43 17.42 12.53 8.37 21.60 10.42 5.33 19.54
#> 96 60 6.1 74 119 54 65 152 112 28 72 163 121
#> 14.54 13.15 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 161 182 176 54.1 151 20 33 31 178 46 200 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 176.1 131 44 80 144 160 120 2 116 151.1 104 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 87 62 152.1 196 174 151.2 21 80.1 132 21.1 135 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 64 147 1 160.1 137.1 48 176.2 21.2 118 82 98 137.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 72.1 173 138 84 178.1 148.1 94 62.1 31.1 103 182.1 80.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 53 165 122.1 173.1 87.1 82.1 67 46.1 160.2 84.1 120.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00913085 0.53664723 0.54290211
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.89267643 0.01226793 0.41947742
#> grade_iii, Cure model
#> 0.97758202
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 93 10.33 1 52 0 1
#> 14 12.89 1 21 0 0
#> 52 10.42 1 52 0 1
#> 111 17.45 1 47 0 1
#> 155 13.08 1 26 0 0
#> 50 10.02 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 105 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 105.1 19.75 1 60 0 0
#> 57 14.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 32 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 140 12.68 1 59 1 0
#> 41 18.02 1 40 1 0
#> 168 23.72 1 70 0 0
#> 93.1 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 86 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 42 12.43 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 26 15.77 1 49 0 1
#> 117 17.46 1 26 0 1
#> 8 18.43 1 32 0 0
#> 76 19.22 1 54 0 1
#> 129 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 157 15.10 1 47 0 0
#> 107 11.18 1 54 1 0
#> 106 16.67 1 49 1 0
#> 153 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 66 22.13 1 53 0 0
#> 86.1 23.81 1 58 0 1
#> 199 19.81 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 16 8.71 1 71 0 1
#> 85 16.44 1 36 0 0
#> 157.1 15.10 1 47 0 0
#> 4.1 17.64 1 NA 0 1
#> 194 22.40 1 38 0 1
#> 97 19.14 1 65 0 1
#> 81 14.06 1 34 0 0
#> 51 18.23 1 83 0 1
#> 26.1 15.77 1 49 0 1
#> 157.2 15.10 1 47 0 0
#> 100 16.07 1 60 0 0
#> 136 21.83 1 43 0 1
#> 111.2 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 150 20.33 1 48 0 0
#> 93.2 10.33 1 52 0 1
#> 79 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 101.1 9.97 1 10 0 1
#> 49.1 12.19 1 48 1 0
#> 18 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 89.1 11.44 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 40 18.00 1 28 1 0
#> 91 5.33 1 61 0 1
#> 199.1 19.81 1 NA 0 1
#> 89.2 11.44 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 166 19.98 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 16.1 8.71 1 71 0 1
#> 15 22.68 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 114.1 13.68 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 167 15.55 1 56 1 0
#> 171 16.57 1 41 0 1
#> 149 8.37 1 33 1 0
#> 45 17.42 1 54 0 1
#> 93.3 10.33 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 171.1 16.57 1 41 0 1
#> 32.1 20.90 1 37 1 0
#> 149.1 8.37 1 33 1 0
#> 58 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 56 12.21 1 60 0 0
#> 39 15.59 1 37 0 1
#> 14.1 12.89 1 21 0 0
#> 170.1 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 37 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 153.1 21.33 1 55 1 0
#> 100.1 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 199.2 19.81 1 NA 0 1
#> 105.2 19.75 1 60 0 0
#> 43 12.10 1 61 0 1
#> 89.3 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 188 16.16 1 46 0 1
#> 184 17.77 1 38 0 0
#> 171.2 16.57 1 41 0 1
#> 163 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 21 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 102 24.00 0 49 0 0
#> 131 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 62 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 21.1 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 48.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 7 24.00 0 37 1 0
#> 82 24.00 0 34 0 0
#> 160 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 19 24.00 0 57 0 1
#> 64 24.00 0 43 0 0
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 162 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 98 24.00 0 34 1 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 119.1 24.00 0 17 0 0
#> 173 24.00 0 19 0 1
#> 87 24.00 0 27 0 0
#> 21.2 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 185.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 144.1 24.00 0 28 0 1
#> 118 24.00 0 44 1 0
#> 31.1 24.00 0 36 0 1
#> 80.1 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 102.1 24.00 0 49 0 0
#> 176.1 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 21.3 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 38 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 161.1 24.00 0 45 0 0
#> 160.1 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 160.2 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 84.1 24.00 0 39 0 1
#> 48.2 24.00 0 31 1 0
#> 131.2 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 144.2 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 31.2 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 142.2 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 138.2 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 83.1 24.00 0 6 0 0
#> 21.4 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.893 NA NA NA
#> 2 age, Cure model 0.0123 NA NA NA
#> 3 grade_ii, Cure model 0.419 NA NA NA
#> 4 grade_iii, Cure model 0.978 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00913 NA NA NA
#> 2 grade_ii, Survival model 0.537 NA NA NA
#> 3 grade_iii, Survival model 0.543 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89268 0.01227 0.41948 0.97758
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 245.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89267643 0.01226793 0.41947742 0.97758202
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00913085 0.53664723 0.54290211
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.865254407 0.695518720 0.844163009 0.370144426 0.674190563 0.547455777
#> [7] 0.188547498 0.370144426 0.188547498 0.642244086 0.053021320 0.140477950
#> [13] 0.002967947 0.716772525 0.315318637 0.025387990 0.865254407 0.979335580
#> [19] 0.012214795 0.684866629 0.906782559 0.769785780 0.547455777 0.526542491
#> [25] 0.359246618 0.282610117 0.250467779 0.034497828 0.158895131 0.663550107
#> [31] 0.600018439 0.822888309 0.412305484 0.111623777 0.917318496 0.791082983
#> [37] 0.091425795 0.012214795 0.453948086 0.937999770 0.453948086 0.600018439
#> [43] 0.081663590 0.261122421 0.652873900 0.304231223 0.526542491 0.600018439
#> [49] 0.505545765 0.101605682 0.370144426 0.168578755 0.865254407 0.484666864
#> [55] 0.631589390 0.917318496 0.791082983 0.589501331 0.738027682 0.043493857
#> [61] 0.326333678 0.989667036 0.071643932 0.178463981 0.844163009 0.937999770
#> [67] 0.062084178 0.716772525 0.453948086 0.578966687 0.423022917 0.958726772
#> [73] 0.401562002 0.865254407 0.282610117 0.423022917 0.140477950 0.958726772
#> [79] 0.239790000 0.219178738 0.780403736 0.568427129 0.695518720 0.219178738
#> [85] 0.833531780 0.748667345 0.130654813 0.111623777 0.505545765 0.271798615
#> [91] 0.188547498 0.812238704 0.348229432 0.748667345 0.495120700 0.337229446
#> [97] 0.423022917 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 93 14 52 111 155 125 105 111.1 105.1 57 63 32 24
#> 10.33 12.89 10.42 17.45 13.08 15.65 19.75 17.45 19.75 14.46 22.77 20.90 23.89
#> 140 41 168 93.1 25 86 123 61 42 125.1 26 117 8
#> 12.68 18.02 23.72 10.33 6.32 23.81 13.00 10.12 12.43 15.65 15.77 17.46 18.43
#> 76 129 68 60 157 107 106 153 101 49 66 86.1 192
#> 19.22 23.41 20.62 13.15 15.10 11.18 16.67 21.33 9.97 12.19 22.13 23.81 16.44
#> 16 85 157.1 194 97 81 51 26.1 157.2 100 136 111.2 150
#> 8.71 16.44 15.10 22.40 19.14 14.06 18.23 15.77 15.10 16.07 21.83 17.45 20.33
#> 93.2 79 96 101.1 49.1 18 154 113 40 91 169 166 52.1
#> 10.33 16.23 14.54 9.97 12.19 15.21 12.63 22.86 18.00 5.33 22.41 19.98 10.42
#> 16.1 15 140.1 192.1 167 171 149 45 93.3 8.1 171.1 32.1 149.1
#> 8.71 22.68 12.68 16.44 15.55 16.57 8.37 17.42 10.33 18.43 16.57 20.90 8.37
#> 58 170 56 39 14.1 170.1 159 37 90 153.1 100.1 179 105.2
#> 19.34 19.54 12.21 15.59 12.89 19.54 10.55 12.52 20.94 21.33 16.07 18.63 19.75
#> 43 110 37.1 188 184 171.2 163 148 176 147 21 48 161
#> 12.10 17.56 12.52 16.16 17.77 16.57 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 131 178 193 62 142 21.1 138 147.1 48.1 1 7 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 54 19 64 116 152 94 162 119 98 44 144 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 103 119.1 173 87 21.2 80 151 185.1 31 144.1 118 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 191 102.1 176.1 2 21.3 12 38 131.1 142.1 83 132 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 138.1 47 84 28 67 160.2 35 75 84.1 48.2 131.2 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 122 144.2 33 31.2 178.1 143 142.2 95 138.2 132.1 9 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 21.4
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01383008 0.80768966 0.36988764
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.83052896 0.01536014 0.30262416
#> grade_iii, Cure model
#> 0.57928438
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 129 23.41 1 53 1 0
#> 78 23.88 1 43 0 0
#> 6 15.64 1 39 0 0
#> 170 19.54 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 164 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 164.1 23.60 1 76 0 1
#> 26 15.77 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 56 12.21 1 60 0 0
#> 55.1 19.34 1 69 0 1
#> 177 12.53 1 75 0 0
#> 36 21.19 1 48 0 1
#> 100 16.07 1 60 0 0
#> 96 14.54 1 33 0 1
#> 30 17.43 1 78 0 0
#> 134 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 36.1 21.19 1 48 0 1
#> 100.1 16.07 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 60.1 13.15 1 38 1 0
#> 168 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 61 10.12 1 36 0 1
#> 58 19.34 1 39 0 0
#> 57 14.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 128 20.35 1 35 0 1
#> 194 22.40 1 38 0 1
#> 164.2 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 8 18.43 1 32 0 0
#> 42 12.43 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 134.1 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 58.1 19.34 1 39 0 0
#> 164.3 23.60 1 76 0 1
#> 180 14.82 1 37 0 0
#> 145 10.07 1 65 1 0
#> 93.1 10.33 1 52 0 1
#> 127 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 57.1 14.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 117 17.46 1 26 0 1
#> 175 21.91 1 43 0 0
#> 171.1 16.57 1 41 0 1
#> 8.1 18.43 1 32 0 0
#> 145.1 10.07 1 65 1 0
#> 150 20.33 1 48 0 0
#> 197 21.60 1 69 1 0
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 179 18.63 1 42 0 0
#> 187.1 9.92 1 39 1 0
#> 197.1 21.60 1 69 1 0
#> 181 16.46 1 45 0 1
#> 123.1 13.00 1 44 1 0
#> 69 23.23 1 25 0 1
#> 188 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 43.1 12.10 1 61 0 1
#> 41 18.02 1 40 1 0
#> 58.2 19.34 1 39 0 0
#> 41.1 18.02 1 40 1 0
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 171.2 16.57 1 41 0 1
#> 179.1 18.63 1 42 0 0
#> 177.1 12.53 1 75 0 0
#> 125.1 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 133 14.65 1 57 0 0
#> 189 10.51 1 NA 1 0
#> 155.1 13.08 1 26 0 0
#> 175.1 21.91 1 43 0 0
#> 91 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 107 11.18 1 54 1 0
#> 127.1 3.53 1 62 0 1
#> 150.1 20.33 1 48 0 0
#> 164.4 23.60 1 76 0 1
#> 79 16.23 1 54 1 0
#> 106 16.67 1 49 1 0
#> 114.1 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 113 22.86 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 61.1 10.12 1 36 0 1
#> 197.2 21.60 1 69 1 0
#> 60.2 13.15 1 38 1 0
#> 149 8.37 1 33 1 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 33 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 28 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 28.1 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 20 24.00 0 46 1 0
#> 17 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 182.1 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 1 24.00 0 23 1 0
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 182.2 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 44.1 24.00 0 56 0 0
#> 53.1 24.00 0 32 0 1
#> 44.2 24.00 0 56 0 0
#> 35.1 24.00 0 51 0 0
#> 75.1 24.00 0 21 1 0
#> 31 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 196.1 24.00 0 19 0 0
#> 1.1 24.00 0 23 1 0
#> 182.3 24.00 0 35 0 0
#> 142.1 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 31.1 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 120 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 109.2 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 152.2 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 19.1 24.00 0 57 0 1
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 1.2 24.00 0 23 1 0
#> 172.1 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 120.1 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 163 24.00 0 66 0 0
#> 31.2 24.00 0 36 0 1
#> 65.1 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 132.2 24.00 0 55 0 0
#> 2 24.00 0 9 0 0
#> 198.1 24.00 0 66 0 1
#> 35.2 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.831 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model 0.303 NA NA NA
#> 4 grade_iii, Cure model 0.579 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0138 NA NA NA
#> 2 grade_ii, Survival model 0.808 NA NA NA
#> 3 grade_iii, Survival model 0.370 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83053 0.01536 0.30262 0.57928
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 258.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83052896 0.01536014 0.30262416 0.57928438
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01383008 0.80768966 0.36988764
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3671531858 0.0339840762 0.0040534786 0.5381287045 0.1906499165
#> [6] 0.2086246263 0.0115796179 0.7074813352 0.6511581691 0.0115796179
#> [11] 0.5052222225 0.5604335306 0.7871410105 0.2086246263 0.7527744516
#> [16] 0.1320650816 0.4835608824 0.5940805810 0.3566617800 0.3160223015
#> [21] 0.7300982031 0.1320650816 0.4835608824 0.1906499165 0.9405258191
#> [26] 0.4307197700 0.8338980088 0.9169176475 0.6511581691 0.0072153455
#> [31] 0.6395807679 0.8693794729 0.2086246263 0.6054224575 0.3463701788
#> [36] 0.1643928823 0.0652218660 0.0115796179 0.5492849360 0.1320650816
#> [41] 0.2749061545 0.7755984590 0.8457156649 0.3160223015 0.3884417334
#> [46] 0.2086246263 0.0115796179 0.5715514252 0.8931209550 0.8457156649
#> [51] 0.9761443124 0.0583365638 0.6054224575 0.0339840762 0.1558233373
#> [56] 0.7987797982 0.3361527643 0.0860380505 0.3884417334 0.2749061545
#> [61] 0.8931209550 0.1730109878 0.1012847170 0.0007469168 0.0007469168
#> [66] 0.5162347772 0.2546879405 0.9169176475 0.1012847170 0.4198988629
#> [71] 0.7074813352 0.0456062970 0.4728790938 0.1239597346 0.7987797982
#> [76] 0.2956709554 0.2086246263 0.2956709554 0.6847040709 0.6280814571
#> [81] 0.0652218660 0.3884417334 0.2546879405 0.7527744516 0.5162347772
#> [86] 0.4516124215 0.5827566261 0.6847040709 0.0860380505 0.9642555141
#> [91] 0.7414970699 0.8221428483 0.9761443124 0.1730109878 0.0115796179
#> [96] 0.4622534270 0.3778182669 0.0786610247 0.0518245654 0.4307197700
#> [101] 0.8693794729 0.1012847170 0.6511581691 0.9524217717 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 23 129 78 6 170 55 164 123 60 164.1 26 18 56
#> 16.92 23.41 23.88 15.64 19.54 19.34 23.60 13.00 13.15 23.60 15.77 15.21 12.21
#> 55.1 177 36 100 96 30 134 140 36.1 100.1 170.1 183 192
#> 19.34 12.53 21.19 16.07 14.54 17.43 17.81 12.68 21.19 16.07 19.54 9.24 16.44
#> 10 187 60.1 168 81 61 58 57 111 128 194 164.2 167
#> 10.53 9.92 13.15 23.72 14.06 10.12 19.34 14.46 17.45 20.35 22.40 23.60 15.55
#> 99 8 42 93 134.1 171 58.1 164.3 180 145 93.1 127 15
#> 21.19 18.43 12.43 10.33 17.81 16.57 19.34 23.60 14.82 10.07 10.33 3.53 22.68
#> 57.1 129.1 68 43 117 175 171.1 8.1 145.1 150 197 24 24.1
#> 14.46 23.41 20.62 12.10 17.46 21.91 16.57 18.43 10.07 20.33 21.60 23.89 23.89
#> 125 179 187.1 197.1 181 123.1 69 188 139 43.1 41 58.2 41.1
#> 15.65 18.63 9.92 21.60 16.46 13.00 23.23 16.16 21.49 12.10 18.02 19.34 18.02
#> 155 13 194.1 171.2 179.1 177.1 125.1 5 133 155.1 175.1 91 154
#> 13.08 14.34 22.40 16.57 18.63 12.53 15.65 16.43 14.65 13.08 21.91 5.33 12.63
#> 107 127.1 150.1 164.4 79 106 66 113 192.1 61.1 197.2 60.2 149
#> 11.18 3.53 20.33 23.60 16.23 16.67 22.13 22.86 16.44 10.12 21.60 13.15 8.37
#> 152 53 33 147 83 135 28 172 75 28.1 54 109 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 17 35 19 182.1 143 132 1 44 98 196 182.2 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 142 122 109.1 44.1 53.1 44.2 35.1 75.1 31 27 196.1 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.3 142.1 178 146 198 31.1 152.1 178.1 38 72 151 11 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 48 11.1 71 109.2 65 146.1 137 137.1 17.1 152.2 176 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 84 1.2 172.1 87 116 120.1 132.1 21 112 144 163 31.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 131 48.1 193 132.2 2 198.1 35.2 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004835696 0.715277889 0.397909105
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.4934279065 0.0008963844 0.5748565093
#> grade_iii, Cure model
#> 1.4123348758
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 13 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 39 15.59 1 37 0 1
#> 32 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 166 19.98 1 48 0 0
#> 66 22.13 1 53 0 0
#> 114 13.68 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 60 13.15 1 38 1 0
#> 13.1 14.34 1 54 0 1
#> 110 17.56 1 65 0 1
#> 134 17.81 1 47 1 0
#> 140 12.68 1 59 1 0
#> 8 18.43 1 32 0 0
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 43 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 68 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 171 16.57 1 41 0 1
#> 133 14.65 1 57 0 0
#> 13.2 14.34 1 54 0 1
#> 81 14.06 1 34 0 0
#> 153 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 113 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 139 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 86 23.81 1 58 0 1
#> 56 12.21 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 188.1 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 199.1 19.81 1 NA 0 1
#> 51 18.23 1 83 0 1
#> 179 18.63 1 42 0 0
#> 24 23.89 1 38 0 0
#> 40 18.00 1 28 1 0
#> 127 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 99 21.19 1 38 0 1
#> 117 17.46 1 26 0 1
#> 175 21.91 1 43 0 0
#> 184 17.77 1 38 0 0
#> 105 19.75 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 70 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 114.1 13.68 1 NA 0 0
#> 8.1 18.43 1 32 0 0
#> 15 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 133.1 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 81.1 14.06 1 34 0 0
#> 29 15.45 1 68 1 0
#> 26 15.77 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 168 23.72 1 70 0 0
#> 166.1 19.98 1 48 0 0
#> 188.2 16.16 1 46 0 1
#> 42.1 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 181 16.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 23 16.92 1 61 0 0
#> 29.1 15.45 1 68 1 0
#> 127.1 3.53 1 62 0 1
#> 86.1 23.81 1 58 0 1
#> 8.2 18.43 1 32 0 0
#> 99.1 21.19 1 38 0 1
#> 68.1 20.62 1 44 0 0
#> 30.2 17.43 1 78 0 0
#> 108 18.29 1 39 0 1
#> 139.1 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 158 20.14 1 74 1 0
#> 171.1 16.57 1 41 0 1
#> 89.1 11.44 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 37 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 111 17.45 1 47 0 1
#> 90.1 20.94 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 32.1 20.90 1 37 1 0
#> 199.2 19.81 1 NA 0 1
#> 194.1 22.40 1 38 0 1
#> 39.1 15.59 1 37 0 1
#> 40.1 18.00 1 28 1 0
#> 188.3 16.16 1 46 0 1
#> 192.2 16.44 1 31 1 0
#> 106 16.67 1 49 1 0
#> 149 8.37 1 33 1 0
#> 164 23.60 1 76 0 1
#> 90.2 20.94 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 159.1 10.55 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 93 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 128 20.35 1 35 0 1
#> 142 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 178.1 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 44.1 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 98 24.00 0 34 1 0
#> 198 24.00 0 66 0 1
#> 185 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 98.1 24.00 0 34 1 0
#> 44.2 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 112 24.00 0 61 0 0
#> 75 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 2.1 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 162.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 112.1 24.00 0 61 0 0
#> 172.1 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 62.1 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 34.1 24.00 0 36 0 0
#> 198.1 24.00 0 66 0 1
#> 143 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 122.1 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 48.1 24.00 0 31 1 0
#> 44.3 24.00 0 56 0 0
#> 138 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 102.1 24.00 0 49 0 0
#> 71.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 67.2 24.00 0 25 0 0
#> 103.1 24.00 0 56 1 0
#> 7.1 24.00 0 37 1 0
#> 162.2 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 17 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 172.2 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 46.1 24.00 0 71 0 0
#> 112.2 24.00 0 61 0 0
#> 27 24.00 0 63 1 0
#> 112.3 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 131.2 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.493 NA NA NA
#> 2 age, Cure model 0.000896 NA NA NA
#> 3 grade_ii, Cure model 0.575 NA NA NA
#> 4 grade_iii, Cure model 1.41 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00484 NA NA NA
#> 2 grade_ii, Survival model 0.715 NA NA NA
#> 3 grade_iii, Survival model 0.398 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4934279 0.0008964 0.5748565 1.4123349
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4934279065 0.0008963844 0.5748565093 1.4123348758
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004835696 0.715277889 0.397909105
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.909285184 0.773019970 0.614328034 0.711995067 0.272464264 0.078495801
#> [7] 0.332141527 0.162492828 0.538839775 0.816147662 0.773019970 0.501128563
#> [13] 0.482001593 0.824800148 0.392549883 0.926074698 0.659274009 0.875705105
#> [19] 0.241902064 0.292174730 0.850413923 0.586180232 0.755646803 0.773019970
#> [25] 0.798806139 0.209433007 0.362071926 0.102473748 0.017232280 0.187012864
#> [31] 0.833404146 0.031655424 0.867233400 0.659274009 0.650278160 0.442703619
#> [37] 0.382371029 0.005181327 0.462858865 0.983798740 0.090630905 0.452858055
#> [43] 0.220611544 0.510691736 0.174671929 0.491549459 0.351950979 0.538839775
#> [49] 0.975650598 0.694170205 0.942700906 0.641210204 0.392549883 0.114529162
#> [55] 0.755646803 0.372241750 0.951014669 0.798806139 0.738369345 0.703092500
#> [61] 0.729581916 0.052908807 0.332141527 0.659274009 0.850413923 0.951014669
#> [67] 0.604915662 0.884167935 0.567060063 0.738369345 0.983798740 0.031655424
#> [73] 0.392549883 0.220611544 0.292174730 0.538839775 0.422629251 0.187012864
#> [79] 0.892584458 0.322209305 0.586180232 0.614328034 0.841932752 0.139423765
#> [85] 0.529421724 0.241902064 0.510691736 0.272464264 0.139423765 0.711995067
#> [91] 0.462858865 0.659274009 0.614328034 0.576668750 0.967449814 0.065736615
#> [97] 0.241902064 0.422629251 0.892584458 0.926074698 0.917685996 0.126854289
#> [103] 0.312143806 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 10 13 192 39 32 69 166 66 30 60 13.1 110 134
#> 10.53 14.34 16.44 15.59 20.90 23.23 19.98 22.13 17.43 13.15 14.34 17.56 17.81
#> 140 8 61 188 43 90 68 42 171 133 13.2 81 153
#> 12.68 18.43 10.12 16.16 12.10 20.94 20.62 12.43 16.57 14.65 14.34 14.06 21.33
#> 58 113 78 139 154 86 56 188.1 79 51 179 24 40
#> 19.34 22.86 23.88 21.49 12.63 23.81 12.21 16.16 16.23 18.23 18.63 23.89 18.00
#> 127 92 41 99 117 175 184 105 30.1 70 100 145 5
#> 3.53 22.92 18.02 21.19 17.46 21.91 17.77 19.75 17.43 7.38 16.07 10.07 16.43
#> 8.1 15 133.1 76 101 81.1 29 26 167 168 166.1 188.2 42.1
#> 18.43 22.68 14.65 19.22 9.97 14.06 15.45 15.77 15.55 23.72 19.98 16.16 12.43
#> 101.1 181 107 23 29.1 127.1 86.1 8.2 99.1 68.1 30.2 108 139.1
#> 9.97 16.46 11.18 16.92 15.45 3.53 23.81 18.43 21.19 20.62 17.43 18.29 21.49
#> 159 158 171.1 192.1 37 194 111 90.1 117.1 32.1 194.1 39.1 40.1
#> 10.55 20.14 16.57 16.44 12.52 22.40 17.45 20.94 17.46 20.90 22.40 15.59 18.00
#> 188.3 192.2 106 149 164 90.2 108.1 159.1 61.1 93 169 128 142
#> 16.16 16.44 16.67 8.37 23.60 20.94 18.29 10.55 10.12 10.33 22.41 20.35 24.00
#> 178 147 44 172 178.1 72 44.1 12 98 198 185 151 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 64 144 98.1 44.2 102 112 75 20 135 7 67 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 122 103 34 21 47 135.1 46 80 132 131 131.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 67.1 162 156 144.1 162.1 176 84 112.1 172.1 87 62 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 191 34.1 198.1 143 109 122.1 176.1 173 19 74 48.1 44.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 31 1 102.1 71.1 163 174 67.2 103.1 7.1 162.2 151.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 172.2 33 46.1 112.2 27 112.3 22 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006449145 0.306227372 0.095449619
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.328771244 -0.001411763 -0.335857984
#> grade_iii, Cure model
#> 0.004229956
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 170 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 179 18.63 1 42 0 0
#> 61 10.12 1 36 0 1
#> 68 20.62 1 44 0 0
#> 133 14.65 1 57 0 0
#> 89 11.44 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 79 16.23 1 54 1 0
#> 66 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 10 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 134 17.81 1 47 1 0
#> 177 12.53 1 75 0 0
#> 81 14.06 1 34 0 0
#> 181 16.46 1 45 0 1
#> 181.1 16.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 16 8.71 1 71 0 1
#> 49.1 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 117 17.46 1 26 0 1
#> 39 15.59 1 37 0 1
#> 180.1 14.82 1 37 0 0
#> 18 15.21 1 49 1 0
#> 125.1 15.65 1 67 1 0
#> 184.1 17.77 1 38 0 0
#> 49.2 12.19 1 48 1 0
#> 88 18.37 1 47 0 0
#> 78 23.88 1 43 0 0
#> 190.1 20.81 1 42 1 0
#> 153 21.33 1 55 1 0
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 195.1 11.76 1 NA 1 0
#> 184.2 17.77 1 38 0 0
#> 167 15.55 1 56 1 0
#> 111 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 155 13.08 1 26 0 0
#> 179.1 18.63 1 42 0 0
#> 192 16.44 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 89.1 11.44 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 13.1 14.34 1 54 0 1
#> 89.2 11.44 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 101 9.97 1 10 0 1
#> 197 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 183 9.24 1 67 1 0
#> 70 7.38 1 30 1 0
#> 85 16.44 1 36 0 0
#> 133.1 14.65 1 57 0 0
#> 23 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 101.1 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 128 20.35 1 35 0 1
#> 4.1 17.64 1 NA 0 1
#> 192.1 16.44 1 31 1 0
#> 129 23.41 1 53 1 0
#> 199.1 19.81 1 NA 0 1
#> 179.3 18.63 1 42 0 0
#> 171 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 197.1 21.60 1 69 1 0
#> 76 19.22 1 54 0 1
#> 23.1 16.92 1 61 0 0
#> 52.1 10.42 1 52 0 1
#> 159 10.55 1 50 0 1
#> 157 15.10 1 47 0 0
#> 18.1 15.21 1 49 1 0
#> 128.1 20.35 1 35 0 1
#> 5 16.43 1 51 0 1
#> 194.1 22.40 1 38 0 1
#> 81.1 14.06 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 190.2 20.81 1 42 1 0
#> 14.1 12.89 1 21 0 0
#> 175.1 21.91 1 43 0 0
#> 56 12.21 1 60 0 0
#> 26 15.77 1 49 0 1
#> 130.1 16.47 1 53 0 1
#> 14.2 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 177.2 12.53 1 75 0 0
#> 92.1 22.92 1 47 0 1
#> 14.3 12.89 1 21 0 0
#> 51.1 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 68.2 20.62 1 44 0 0
#> 127 3.53 1 62 0 1
#> 76.1 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 60.1 13.15 1 38 1 0
#> 184.3 17.77 1 38 0 0
#> 166.1 19.98 1 48 0 0
#> 85.1 16.44 1 36 0 0
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 146 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 94.1 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 198.1 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 172.1 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 193.1 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 47 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 200.1 24.00 0 64 0 0
#> 119 24.00 0 17 0 0
#> 47.1 24.00 0 38 0 1
#> 3.1 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 119.1 24.00 0 17 0 0
#> 11.1 24.00 0 42 0 1
#> 1.1 24.00 0 23 1 0
#> 161.1 24.00 0 45 0 0
#> 65.1 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 75.1 24.00 0 21 1 0
#> 186 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 135.1 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 31.1 24.00 0 36 0 1
#> 200.2 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 122 24.00 0 66 0 0
#> 198.2 24.00 0 66 0 1
#> 87.1 24.00 0 27 0 0
#> 27 24.00 0 63 1 0
#> 33.1 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 178.1 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 95.2 24.00 0 68 0 1
#> 163.1 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 146.1 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 67 24.00 0 25 0 0
#> 122.1 24.00 0 66 0 0
#> 200.3 24.00 0 64 0 0
#> 27.1 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 33.2 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 165.1 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.329 NA NA NA
#> 2 age, Cure model -0.00141 NA NA NA
#> 3 grade_ii, Cure model -0.336 NA NA NA
#> 4 grade_iii, Cure model 0.00423 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00645 NA NA NA
#> 2 grade_ii, Survival model 0.306 NA NA NA
#> 3 grade_iii, Survival model 0.0954 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.328771 -0.001412 -0.335858 0.004230
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 258.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.328771244 -0.001411763 -0.335857984 0.004229956
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006449145 0.306227372 0.095449619
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.638295921 0.205571468 0.509757656 0.232616170 0.895493582 0.146197213
#> [7] 0.616537422 0.307104175 0.488577689 0.073479867 0.122474317 0.278079590
#> [13] 0.396051339 0.860965447 0.595012647 0.297322677 0.770372271 0.660221432
#> [19] 0.416607854 0.416607854 0.815573659 0.964953158 0.815573659 0.682291308
#> [25] 0.345416145 0.530864133 0.595012647 0.562979215 0.509757656 0.307104175
#> [31] 0.815573659 0.268525309 0.005672140 0.122474317 0.113934707 0.030487345
#> [37] 0.307104175 0.541553044 0.355440688 0.188031862 0.895493582 0.704316317
#> [43] 0.232616170 0.437345626 0.552253249 0.146197213 0.638295921 0.872482585
#> [49] 0.930213006 0.097551913 0.051095639 0.726448216 0.081523323 0.953314694
#> [55] 0.976634458 0.437345626 0.616537422 0.365518544 0.232616170 0.058715344
#> [61] 0.930213006 0.016777037 0.170918087 0.437345626 0.023590409 0.232616170
#> [67] 0.385754502 0.001580686 0.037491698 0.097551913 0.214602310 0.365518544
#> [73] 0.872482585 0.849478566 0.584234697 0.562979215 0.170918087 0.478019351
#> [79] 0.058715344 0.660221432 0.770372271 0.122474317 0.726448216 0.081523323
#> [85] 0.804113370 0.499145434 0.396051339 0.726448216 0.918580416 0.770372271
#> [91] 0.037491698 0.726448216 0.278079590 0.704316317 0.146197213 0.988299107
#> [97] 0.214602310 0.010856017 0.682291308 0.307104175 0.188031862 0.437345626
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 13 170 125 179 61 68 133 184 79 66 190 51 130
#> 14.34 19.54 15.65 18.63 10.12 20.62 14.65 17.77 16.23 22.13 20.81 18.23 16.47
#> 10 180 134 177 81 181 181.1 49 16 49.1 60 117 39
#> 10.53 14.82 17.81 12.53 14.06 16.46 16.46 12.19 8.71 12.19 13.15 17.46 15.59
#> 180.1 18 125.1 184.1 49.2 88 78 190.1 153 69 184.2 167 111
#> 14.82 15.21 15.65 17.77 12.19 18.37 23.88 20.81 21.33 23.23 17.77 15.55 17.45
#> 166 61.1 155 179.1 192 29 68.1 13.1 52 101 197 15 14
#> 19.98 10.12 13.08 18.63 16.44 15.45 20.62 14.34 10.42 9.97 21.60 22.68 12.89
#> 175 183 70 85 133.1 23 179.2 194 101.1 168 128 192.1 129
#> 21.91 9.24 7.38 16.44 14.65 16.92 18.63 22.40 9.97 23.72 20.35 16.44 23.41
#> 179.3 171 24 92 197.1 76 23.1 52.1 159 157 18.1 128.1 5
#> 18.63 16.57 23.89 22.92 21.60 19.22 16.92 10.42 10.55 15.10 15.21 20.35 16.43
#> 194.1 81.1 177.1 190.2 14.1 175.1 56 26 130.1 14.2 145 177.2 92.1
#> 22.40 14.06 12.53 20.81 12.89 21.91 12.21 15.77 16.47 12.89 10.07 12.53 22.92
#> 14.3 51.1 155.1 68.2 127 76.1 86 60.1 184.3 166.1 85.1 94 178
#> 12.89 18.23 13.08 20.62 3.53 19.22 23.81 13.15 17.77 19.98 16.44 24.00 24.00
#> 31 193 48 142 152 173 83 3 200 146 151 162 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 1 147 94.1 198 172 95 20 75 148 198.1 11 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 135 193.1 161 47 163 185 65 191 200.1 119 47.1 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 119.1 11.1 1.1 161.1 65.1 95.1 165 84 75.1 186 33 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 53 31.1 200.2 87 122 198.2 87.1 27 33.1 72 178.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.2 163.1 176.1 146.1 44 67 122.1 200.3 27.1 9 173.2 109 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 33.2 104 165.1 131 132
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009977124 0.770964341 0.310149982
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.67999037 0.01261246 0.52505364
#> grade_iii, Cure model
#> 0.32667692
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 168 23.72 1 70 0 0
#> 90 20.94 1 50 0 1
#> 97 19.14 1 65 0 1
#> 130 16.47 1 53 0 1
#> 149 8.37 1 33 1 0
#> 86 23.81 1 58 0 1
#> 50 10.02 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 42 12.43 1 49 0 1
#> 50.1 10.02 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 91 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 149.1 8.37 1 33 1 0
#> 6 15.64 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 50.2 10.02 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 85 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 110 17.56 1 65 0 1
#> 90.1 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 41 18.02 1 40 1 0
#> 133 14.65 1 57 0 0
#> 45 17.42 1 54 0 1
#> 55 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 51.1 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 168.1 23.72 1 70 0 0
#> 14 12.89 1 21 0 0
#> 166 19.98 1 48 0 0
#> 158 20.14 1 74 1 0
#> 37 12.52 1 57 1 0
#> 8 18.43 1 32 0 0
#> 37.1 12.52 1 57 1 0
#> 41.1 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 187 9.92 1 39 1 0
#> 79 16.23 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 81 14.06 1 34 0 0
#> 100 16.07 1 60 0 0
#> 45.1 17.42 1 54 0 1
#> 184.1 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 91.1 5.33 1 61 0 1
#> 111 17.45 1 47 0 1
#> 149.2 8.37 1 33 1 0
#> 13 14.34 1 54 0 1
#> 85.1 16.44 1 36 0 0
#> 90.2 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 18 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 139 21.49 1 63 1 0
#> 168.2 23.72 1 70 0 0
#> 124 9.73 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 187.1 9.92 1 39 1 0
#> 42.1 12.43 1 49 0 1
#> 10 10.53 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 50.3 10.02 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 179 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 149.3 8.37 1 33 1 0
#> 41.2 18.02 1 40 1 0
#> 97.1 19.14 1 65 0 1
#> 149.4 8.37 1 33 1 0
#> 117 17.46 1 26 0 1
#> 81.1 14.06 1 34 0 0
#> 50.4 10.02 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 113.1 22.86 1 34 0 0
#> 56.1 12.21 1 60 0 0
#> 32 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 41.3 18.02 1 40 1 0
#> 58 19.34 1 39 0 0
#> 32.1 20.90 1 37 1 0
#> 30 17.43 1 78 0 0
#> 10.1 10.53 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 134 17.81 1 47 1 0
#> 16 8.71 1 71 0 1
#> 93 10.33 1 52 0 1
#> 79.1 16.23 1 54 1 0
#> 58.1 19.34 1 39 0 0
#> 76.1 19.22 1 54 0 1
#> 79.2 16.23 1 54 1 0
#> 90.3 20.94 1 50 0 1
#> 106.1 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 29 15.45 1 68 1 0
#> 52.2 10.42 1 52 0 1
#> 155 13.08 1 26 0 0
#> 113.2 22.86 1 34 0 0
#> 135 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 65 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 148 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 12.1 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 12.2 24.00 0 63 0 0
#> 2 24.00 0 9 0 0
#> 121 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 19 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 2.1 24.00 0 9 0 0
#> 83 24.00 0 6 0 0
#> 143 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 64.1 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 2.2 24.00 0 9 0 0
#> 162.2 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 72.1 24.00 0 40 0 1
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 118.1 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 182 24.00 0 35 0 0
#> 87 24.00 0 27 0 0
#> 48.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 152 24.00 0 36 0 1
#> 19.1 24.00 0 57 0 1
#> 173.2 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 83.1 24.00 0 6 0 0
#> 162.3 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 2.3 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 156.1 24.00 0 50 1 0
#> 144.1 24.00 0 28 0 1
#> 109.1 24.00 0 48 0 0
#> 17 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 196.1 24.00 0 19 0 0
#> 143.1 24.00 0 51 0 0
#> 62.2 24.00 0 71 0 0
#> 72.2 24.00 0 40 0 1
#> 104 24.00 0 50 1 0
#> 165.1 24.00 0 47 0 0
#> 120.2 24.00 0 68 0 1
#> 95.1 24.00 0 68 0 1
#> 62.3 24.00 0 71 0 0
#> 62.4 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 74 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#> 144.2 24.00 0 28 0 1
#> 152.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.680 NA NA NA
#> 2 age, Cure model 0.0126 NA NA NA
#> 3 grade_ii, Cure model 0.525 NA NA NA
#> 4 grade_iii, Cure model 0.327 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00998 NA NA NA
#> 2 grade_ii, Survival model 0.771 NA NA NA
#> 3 grade_iii, Survival model 0.310 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.67999 0.01261 0.52505 0.32668
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 259 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.67999037 0.01261246 0.52505364 0.32667692
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009977124 0.770964341 0.310149982
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4880555975 0.0139697620 0.1132896251 0.2490047435 0.4982949845
#> [6] 0.9299494384 0.0086774727 0.0407872893 0.7738538695 0.1666842208
#> [11] 0.0009521738 0.2883870221 0.8152476728 0.9796858335 0.5085758663
#> [16] 0.9299494384 0.5890224682 0.5890224682 0.0496528224 0.4678311959
#> [21] 0.5085758663 0.3088257686 0.4574596233 0.3969126174 0.1132896251
#> [26] 0.7326885519 0.3294969404 0.6400815053 0.4371590549 0.2027621492
#> [31] 0.3772639032 0.3088257686 0.1756573366 0.0139697620 0.7223578900
#> [36] 0.1936245183 0.1846481375 0.7533675865 0.2783144013 0.7533675865
#> [41] 0.3294969404 0.0322018784 0.8986902669 0.5388097985 0.0041041810
#> [46] 0.6709834437 0.5686072614 0.4371590549 0.3772639032 0.8568874936
#> [51] 0.0850403587 0.7944293282 0.9796858335 0.4169421337 0.9299494384
#> [56] 0.6606538316 0.5085758663 0.1132896251 0.6916654603 0.6198350694
#> [61] 0.5788001312 0.0949845803 0.0139697620 0.8568874936 0.8986902669
#> [66] 0.7738538695 0.8360753917 0.6198350694 0.7429901681 0.0949845803
#> [71] 0.2683404693 0.0752259097 0.9299494384 0.3294969404 0.2490047435
#> [76] 0.9299494384 0.4069337838 0.6709834437 0.6503571235 0.2985931025
#> [81] 0.0496528224 0.7944293282 0.1488271122 0.2300911376 0.3294969404
#> [86] 0.2027621492 0.1488271122 0.4269858886 0.8360753917 0.6916654603
#> [91] 0.3674713756 0.9194640654 0.8881284604 0.5388097985 0.2027621492
#> [96] 0.2300911376 0.5388097985 0.1132896251 0.4678311959 0.8256786960
#> [101] 0.6095170924 0.8568874936 0.7120550820 0.0496528224 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 171 168 90 97 130 149 86 92 42 190 24 88 49
#> 16.57 23.72 20.94 19.14 16.47 8.37 23.81 22.92 12.43 20.81 23.89 18.37 12.19
#> 91 192 149.1 6 6.1 113 106 85 51 23 110 90.1 140
#> 5.33 16.44 8.37 15.64 15.64 22.86 16.67 16.44 18.23 16.92 17.56 20.94 12.68
#> 41 133 45 55 184 51.1 128 168.1 14 166 158 37 8
#> 18.02 14.65 17.42 19.34 17.77 18.23 20.35 23.72 12.89 19.98 20.14 12.52 18.43
#> 37.1 41.1 164 187 79 78 81 100 45.1 184.1 52 136 56
#> 12.52 18.02 23.60 9.92 16.23 23.88 14.06 16.07 17.42 17.77 10.42 21.83 12.21
#> 91.1 111 149.2 13 85.1 90.2 60 18 26 139 168.2 52.1 187.1
#> 5.33 17.45 8.37 14.34 16.44 20.94 13.15 15.21 15.77 21.49 23.72 10.42 9.92
#> 42.1 10 18.1 177 139.1 179 194 149.3 41.2 97.1 149.4 117 81.1
#> 12.43 10.53 15.21 12.53 21.49 18.63 22.40 8.37 18.02 19.14 8.37 17.46 14.06
#> 57 108 113.1 56.1 32 76 41.3 58 32.1 30 10.1 60.1 134
#> 14.46 18.29 22.86 12.21 20.90 19.22 18.02 19.34 20.90 17.43 10.53 13.15 17.81
#> 16 93 79.1 58.1 76.1 79.2 90.3 106.1 107 29 52.2 155 113.2
#> 8.71 10.33 16.23 19.34 19.22 16.23 20.94 16.67 11.18 15.45 10.42 13.08 22.86
#> 135 65 173 131 31 198 148 12 109 64 12.1 48 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 162 22 191 12.2 2 121 162.1 67 19 72 2.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 156 200 64.1 173.1 2.2 162.2 103 72.1 196 176 118.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 7 38 200.1 182 87 48.1 120 34 178 144 152 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.2 95 163 62.1 165 83.1 162.3 9 2.3 82 156.1 144.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 28 138 120.1 196.1 143.1 62.2 72.2 104 165.1 120.2 95.1 62.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.4 146 116 11 74 116.1 11.1 144.2 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006073692 0.851494881 0.249164891
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00686565 0.01964753 -0.05039212
#> grade_iii, Cure model
#> 0.67484701
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 25 6.32 1 34 1 0
#> 39 15.59 1 37 0 1
#> 105 19.75 1 60 0 0
#> 159 10.55 1 50 0 1
#> 77 7.27 1 67 0 1
#> 69 23.23 1 25 0 1
#> 139 21.49 1 63 1 0
#> 179 18.63 1 42 0 0
#> 179.1 18.63 1 42 0 0
#> 49 12.19 1 48 1 0
#> 8 18.43 1 32 0 0
#> 111 17.45 1 47 0 1
#> 77.1 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 139.1 21.49 1 63 1 0
#> 197 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 175 21.91 1 43 0 0
#> 70 7.38 1 30 1 0
#> 158 20.14 1 74 1 0
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 101 9.97 1 10 0 1
#> 149 8.37 1 33 1 0
#> 57 14.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 59 10.16 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 16 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 70.1 7.38 1 30 1 0
#> 195 11.76 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 24 23.89 1 38 0 0
#> 30 17.43 1 78 0 0
#> 189.1 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 166 19.98 1 48 0 0
#> 127 3.53 1 62 0 1
#> 59.1 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 10 10.53 1 34 0 0
#> 101.1 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 127.1 3.53 1 62 0 1
#> 39.1 15.59 1 37 0 1
#> 127.2 3.53 1 62 0 1
#> 92.1 22.92 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 175.1 21.91 1 43 0 0
#> 96 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 69.1 23.23 1 25 0 1
#> 16.2 8.71 1 71 0 1
#> 134 17.81 1 47 1 0
#> 130.1 16.47 1 53 0 1
#> 25.1 6.32 1 34 1 0
#> 86 23.81 1 58 0 1
#> 164 23.60 1 76 0 1
#> 30.1 17.43 1 78 0 0
#> 108 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 97 19.14 1 65 0 1
#> 136 21.83 1 43 0 1
#> 111.1 17.45 1 47 0 1
#> 92.2 22.92 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 134.2 17.81 1 47 1 0
#> 114.1 13.68 1 NA 0 0
#> 50.1 10.02 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 15 22.68 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 149.1 8.37 1 33 1 0
#> 45.1 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 117 17.46 1 26 0 1
#> 108.2 18.29 1 39 0 1
#> 139.2 21.49 1 63 1 0
#> 57.1 14.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 69.2 23.23 1 25 0 1
#> 14 12.89 1 21 0 0
#> 6 15.64 1 39 0 0
#> 58.1 19.34 1 39 0 0
#> 59.2 10.16 1 NA 1 0
#> 57.2 14.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 57.3 14.46 1 45 0 1
#> 10.1 10.53 1 34 0 0
#> 136.1 21.83 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 89 11.44 1 NA 0 0
#> 110.1 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 23.1 16.92 1 61 0 0
#> 113 22.86 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 24.1 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 164.1 23.60 1 76 0 1
#> 179.2 18.63 1 42 0 0
#> 2 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 3 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 116 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 176 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 115 24.00 0 NA 1 0
#> 198.1 24.00 0 66 0 1
#> 178 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 147 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 87 24.00 0 27 0 0
#> 115.1 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 47.1 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 143.1 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 47.2 24.00 0 38 0 1
#> 193.1 24.00 0 45 0 1
#> 53 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 17.1 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 31.1 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 165.1 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 22.1 24.00 0 52 1 0
#> 98.2 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 94.2 24.00 0 51 0 1
#> 21.1 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 1.1 24.00 0 23 1 0
#> 148 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 176.1 24.00 0 43 0 1
#> 48.1 24.00 0 31 1 0
#> 1.2 24.00 0 23 1 0
#> 17.2 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 131 24.00 0 66 0 0
#> 98.3 24.00 0 34 1 0
#> 64.1 24.00 0 43 0 0
#> 178.1 24.00 0 52 1 0
#> 126 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 9 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.01 NA NA NA
#> 2 age, Cure model 0.0196 NA NA NA
#> 3 grade_ii, Cure model -0.0504 NA NA NA
#> 4 grade_iii, Cure model 0.675 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00607 NA NA NA
#> 2 grade_ii, Survival model 0.851 NA NA NA
#> 3 grade_iii, Survival model 0.249 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00687 0.01965 -0.05039 0.67485
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 247.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00686565 0.01964753 -0.05039212 0.67484701
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006073692 0.851494881 0.249164891
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.757815696 0.955358529 0.611591122 0.298475712 0.786717412 0.937179646
#> [7] 0.066503978 0.218145520 0.339312792 0.339312792 0.767537775 0.370059269
#> [13] 0.470602603 0.937179646 0.258393274 0.218145520 0.206725111 0.530733832
#> [19] 0.161015532 0.919052094 0.268774504 0.709643345 0.440776595 0.834569097
#> [25] 0.900577351 0.641423954 0.031786419 0.863065277 0.872481779 0.872481779
#> [31] 0.561329923 0.824957695 0.919052094 0.581534958 0.680524433 0.096460201
#> [37] 0.006036333 0.490421565 0.777168295 0.288401218 0.973229356 0.510547496
#> [43] 0.796272684 0.834569097 0.149551797 0.973229356 0.611591122 0.973229356
#> [49] 0.096460201 0.268774504 0.161015532 0.631432156 0.699878571 0.066503978
#> [55] 0.872481779 0.411552030 0.561329923 0.955358529 0.021272270 0.043691642
#> [61] 0.490421565 0.380659189 0.815353511 0.328956477 0.183851553 0.470602603
#> [67] 0.096460201 0.411552030 0.411552030 0.247996538 0.138072194 0.380659189
#> [73] 0.900577351 0.510547496 0.738571178 0.460601772 0.380659189 0.218145520
#> [79] 0.641423954 0.551160777 0.308655161 0.066503978 0.719302638 0.601580742
#> [85] 0.308655161 0.641423954 0.728977489 0.641423954 0.796272684 0.183851553
#> [91] 0.680524433 0.440776595 0.853590909 0.530733832 0.126829371 0.738571178
#> [97] 0.006036333 0.591605375 0.043691642 0.339312792 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 56 25 39 105 159 77 69 139 179 179.1 49 8 111
#> 12.21 6.32 15.59 19.75 10.55 7.27 23.23 21.49 18.63 18.63 12.19 18.43 17.45
#> 77.1 128 139.1 197 23 175 70 158 123 110 101 149 57
#> 7.27 20.35 21.49 21.60 16.92 21.91 7.38 20.14 13.00 17.56 9.97 8.37 14.46
#> 168 183 16 16.1 130 93 70.1 79 60 92 24 30 107
#> 23.72 9.24 8.71 8.71 16.47 10.33 7.38 16.23 13.15 22.92 23.89 17.43 11.18
#> 166 127 45 10 101.1 194 127.1 39.1 127.2 92.1 158.1 175.1 96
#> 19.98 3.53 17.42 10.53 9.97 22.40 3.53 15.59 3.53 22.92 20.14 21.91 14.54
#> 155 69.1 16.2 134 130.1 25.1 86 164 30.1 108 52 97 136
#> 13.08 23.23 8.71 17.81 16.47 6.32 23.81 23.60 17.43 18.29 10.42 19.14 21.83
#> 111.1 92.2 134.1 134.2 36 15 108.1 149.1 45.1 177 117 108.2 139.2
#> 17.45 22.92 17.81 17.81 21.19 22.68 18.29 8.37 17.42 12.53 17.46 18.29 21.49
#> 57.1 106 58 69.2 14 6 58.1 57.2 140 57.3 10.1 136.1 60.1
#> 14.46 16.67 19.34 23.23 12.89 15.64 19.34 14.46 12.68 14.46 10.53 21.83 13.15
#> 110.1 187 23.1 113 177.1 24.1 125 164.1 179.2 2 38 141 35
#> 17.56 9.92 16.92 22.86 12.53 23.89 15.65 23.60 18.63 24.00 24.00 24.00 24.00
#> 151 31 22 72 144 47 143 191 198 160 142 21 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 3 161 116 17 112 138 196 98 176 80 116.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 198.1 178 71 94.1 147 46 64 87 19 48 119 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 143.1 146 135 47.2 193.1 53 185 98.1 17.1 87.1 31.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 165.1 162 2.1 22.1 98.2 118 82 94.2 21.1 182 1.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 109 176.1 48.1 1.2 17.2 7 131 98.3 64.1 178.1 126 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 20 9 28
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006226997 0.294295928 0.126432413
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91986478 0.01156552 0.53106061
#> grade_iii, Cure model
#> 1.07769566
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 105 19.75 1 60 0 0
#> 52 10.42 1 52 0 1
#> 32 20.90 1 37 1 0
#> 128 20.35 1 35 0 1
#> 189 10.51 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 60 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 79 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 195 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 55.1 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 55.2 19.34 1 69 0 1
#> 77.1 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 195.1 11.76 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 125.2 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 127 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 50 10.02 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 70 7.38 1 30 1 0
#> 43 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 18.1 15.21 1 49 1 0
#> 149.1 8.37 1 33 1 0
#> 181.1 16.46 1 45 0 1
#> 77.2 7.27 1 67 0 1
#> 130 16.47 1 53 0 1
#> 133.1 14.65 1 57 0 0
#> 183 9.24 1 67 1 0
#> 88 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 93 10.33 1 52 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 177 12.53 1 75 0 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 171 16.57 1 41 0 1
#> 114 13.68 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 93.1 10.33 1 52 0 1
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 111.1 17.45 1 47 0 1
#> 49 12.19 1 48 1 0
#> 195.2 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 32.1 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 56.1 12.21 1 60 0 0
#> 139 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 188.1 16.16 1 46 0 1
#> 128.1 20.35 1 35 0 1
#> 177.1 12.53 1 75 0 0
#> 170.1 19.54 1 43 0 1
#> 37 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 18.2 15.21 1 49 1 0
#> 49.1 12.19 1 48 1 0
#> 70.1 7.38 1 30 1 0
#> 125.3 15.65 1 67 1 0
#> 14 12.89 1 21 0 0
#> 86.1 23.81 1 58 0 1
#> 55.3 19.34 1 69 0 1
#> 117.1 17.46 1 26 0 1
#> 77.3 7.27 1 67 0 1
#> 166.1 19.98 1 48 0 0
#> 58 19.34 1 39 0 0
#> 61 10.12 1 36 0 1
#> 93.2 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 32.2 20.90 1 37 1 0
#> 108 18.29 1 39 0 1
#> 14.1 12.89 1 21 0 0
#> 81 14.06 1 34 0 0
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 5 16.43 1 51 0 1
#> 179 18.63 1 42 0 0
#> 97.1 19.14 1 65 0 1
#> 129 23.41 1 53 1 0
#> 69 23.23 1 25 0 1
#> 105.1 19.75 1 60 0 0
#> 149.2 8.37 1 33 1 0
#> 63 22.77 1 31 1 0
#> 52.1 10.42 1 52 0 1
#> 157 15.10 1 47 0 0
#> 9 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 46 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 44.1 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 83.1 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 116 24.00 0 58 0 1
#> 38.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 122 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 28.1 24.00 0 67 1 0
#> 84 24.00 0 39 0 1
#> 71.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 1 24.00 0 23 1 0
#> 116.1 24.00 0 58 0 1
#> 19 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 146.1 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 33.1 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 122.1 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 9.2 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 162 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 122.2 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 47.1 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 126 24.00 0 48 0 0
#> 21.1 24.00 0 47 0 0
#> 20.1 24.00 0 46 1 0
#> 2 24.00 0 9 0 0
#> 11.2 24.00 0 42 0 1
#> 142.1 24.00 0 53 0 0
#> 19.1 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 165.2 24.00 0 47 0 0
#> 38.2 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 12.2 24.00 0 63 0 0
#> 84.1 24.00 0 39 0 1
#> 186 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.920 NA NA NA
#> 2 age, Cure model 0.0116 NA NA NA
#> 3 grade_ii, Cure model 0.531 NA NA NA
#> 4 grade_iii, Cure model 1.08 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00623 NA NA NA
#> 2 grade_ii, Survival model 0.294 NA NA NA
#> 3 grade_iii, Survival model 0.126 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91986 0.01157 0.53106 1.07770
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 251.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91986478 0.01156552 0.53106061 1.07769566
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006226997 0.294295928 0.126432413
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69619794 0.41023943 0.86636418 0.30194890 0.36828818 0.74757712
#> [7] 0.76918635 0.54910801 0.64213929 0.34660399 0.61750262 0.96330025
#> [13] 0.03458569 0.45041350 0.91249881 0.45041350 0.81870787 0.59216587
#> [19] 0.26419268 0.26419268 0.45041350 0.96330025 0.66618730 0.66618730
#> [25] 0.54027800 0.34660399 0.66618730 0.73301817 0.99388297 0.38946038
#> [31] 0.93188465 0.74757712 0.90596068 0.95077049 0.84613294 0.49532959
#> [37] 0.69619794 0.93188465 0.61750262 0.96330025 0.60912041 0.73301817
#> [43] 0.91900380 0.52237638 0.19029937 0.87970006 0.57516588 0.72563943
#> [49] 0.84613294 0.79770348 0.98774063 0.43055272 0.60067095 0.33536179
#> [55] 0.87970006 0.11849086 0.20612966 0.57516588 0.83251184 0.22149921
#> [61] 0.79058790 0.65025640 0.30194890 0.07615163 0.81870787 0.23654867
#> [67] 0.55790028 0.65025640 0.36828818 0.79770348 0.43055272 0.81172297
#> [73] 0.28937722 0.69619794 0.83251184 0.95077049 0.66618730 0.77635444
#> [79] 0.07615163 0.45041350 0.55790028 0.96330025 0.38946038 0.45041350
#> [85] 0.89937445 0.87970006 0.92546138 0.30194890 0.53136086 0.77635444
#> [91] 0.76197116 0.25070954 0.85961104 0.63393101 0.51333906 0.49532959
#> [97] 0.13871653 0.15667930 0.41023943 0.93188465 0.17399775 0.86636418
#> [103] 0.71824120 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 18 105 52 32 128 13 60 184 79 68 181 77 24
#> 15.21 19.75 10.42 20.90 20.35 14.34 13.15 17.77 16.23 20.62 16.46 7.27 23.89
#> 55 187 55.1 56 23 99 99.1 55.2 77.1 125 125.1 40 68.1
#> 19.34 9.92 19.34 12.21 16.92 21.19 21.19 19.34 7.27 15.65 15.65 18.00 20.62
#> 125.2 133 127 166 149 13.1 145 70 43 97 18.1 149.1 181.1
#> 15.65 14.65 3.53 19.98 8.37 14.34 10.07 7.38 12.10 19.14 15.21 8.37 16.46
#> 77.2 130 133.1 183 88 15 93 111 180 43.1 177 91 170
#> 7.27 16.47 14.65 9.24 18.37 22.68 10.33 17.45 14.82 12.10 12.53 5.33 19.54
#> 171 190 93.1 164 66 111.1 49 175 154 188 32.1 86 56.1
#> 16.57 20.81 10.33 23.60 22.13 17.45 12.19 21.91 12.63 16.16 20.90 23.81 12.21
#> 139 117 188.1 128.1 177.1 170.1 37 90 18.2 49.1 70.1 125.3 14
#> 21.49 17.46 16.16 20.35 12.53 19.54 12.52 20.94 15.21 12.19 7.38 15.65 12.89
#> 86.1 55.3 117.1 77.3 166.1 58 61 93.2 16 32.2 108 14.1 81
#> 23.81 19.34 17.46 7.27 19.98 19.34 10.12 10.33 8.71 20.90 18.29 12.89 14.06
#> 153 10 5 179 97.1 129 69 105.1 149.2 63 52.1 157 9
#> 21.33 10.53 16.43 18.63 19.14 23.41 23.23 19.75 8.37 22.77 10.42 15.10 24.00
#> 44 165 12 34 48 38 74 83 46 64 71 142 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 7 44.1 146 119 11 33 83.1 28 148 148.1 116 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 62 182 122 62.1 165.1 121 11.1 28.1 84 71.1 120.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 1 116.1 19 31 146.1 185 47 109 20 172 138 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 95 172.1 54 33.1 196 193 143 122.1 174 9.2 34.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 122.2 87 47.1 12.1 126 21.1 20.1 2 11.2 142.1 19.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 38.2 7.1 94 12.2 84.1 186 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004386588 0.630176104 0.566364964
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.099164180 -0.001680121 -0.172055086
#> grade_iii, Cure model
#> 1.278939420
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 168 23.72 1 70 0 0
#> 23 16.92 1 61 0 0
#> 108 18.29 1 39 0 1
#> 13 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 187 9.92 1 39 1 0
#> 76 19.22 1 54 0 1
#> 39 15.59 1 37 0 1
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 26 15.77 1 49 0 1
#> 106 16.67 1 49 1 0
#> 66 22.13 1 53 0 0
#> 192 16.44 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 15 22.68 1 48 0 0
#> 32 20.90 1 37 1 0
#> 66.1 22.13 1 53 0 0
#> 66.2 22.13 1 53 0 0
#> 42 12.43 1 49 0 1
#> 58 19.34 1 39 0 0
#> 5 16.43 1 51 0 1
#> 59 10.16 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 108.1 18.29 1 39 0 1
#> 96 14.54 1 33 0 1
#> 166 19.98 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 187.1 9.92 1 39 1 0
#> 45 17.42 1 54 0 1
#> 106.1 16.67 1 49 1 0
#> 32.1 20.90 1 37 1 0
#> 114 13.68 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 91 5.33 1 61 0 1
#> 97 19.14 1 65 0 1
#> 117 17.46 1 26 0 1
#> 16 8.71 1 71 0 1
#> 181 16.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 51 18.23 1 83 0 1
#> 187.2 9.92 1 39 1 0
#> 66.3 22.13 1 53 0 0
#> 187.3 9.92 1 39 1 0
#> 97.1 19.14 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 100 16.07 1 60 0 0
#> 96.2 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 164 23.60 1 76 0 1
#> 24 23.89 1 38 0 0
#> 81.1 14.06 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 139 21.49 1 63 1 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 92 22.92 1 47 0 1
#> 59.1 10.16 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 194.1 22.40 1 38 0 1
#> 43 12.10 1 61 0 1
#> 130 16.47 1 53 0 1
#> 197 21.60 1 69 1 0
#> 188 16.16 1 46 0 1
#> 139.1 21.49 1 63 1 0
#> 63 22.77 1 31 1 0
#> 52 10.42 1 52 0 1
#> 57.1 14.46 1 45 0 1
#> 155 13.08 1 26 0 0
#> 124.1 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 127 3.53 1 62 0 1
#> 96.3 14.54 1 33 0 1
#> 128 20.35 1 35 0 1
#> 91.1 5.33 1 61 0 1
#> 128.1 20.35 1 35 0 1
#> 60 13.15 1 38 1 0
#> 59.2 10.16 1 NA 1 0
#> 128.2 20.35 1 35 0 1
#> 101 9.97 1 10 0 1
#> 15.1 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 56.2 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 113 22.86 1 34 0 0
#> 36 21.19 1 48 0 1
#> 127.1 3.53 1 62 0 1
#> 43.1 12.10 1 61 0 1
#> 92.1 22.92 1 47 0 1
#> 125 15.65 1 67 1 0
#> 139.2 21.49 1 63 1 0
#> 100.1 16.07 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 140 12.68 1 59 1 0
#> 37.1 12.52 1 57 1 0
#> 127.2 3.53 1 62 0 1
#> 30 17.43 1 78 0 0
#> 192.1 16.44 1 31 1 0
#> 195.1 11.76 1 NA 1 0
#> 155.1 13.08 1 26 0 0
#> 159 10.55 1 50 0 1
#> 140.1 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 52.1 10.42 1 52 0 1
#> 169.1 22.41 1 46 0 0
#> 49 12.19 1 48 1 0
#> 161 24.00 0 45 0 0
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 82 24.00 0 34 0 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 121.1 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 53 24.00 0 32 0 1
#> 54 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 141.1 24.00 0 44 1 0
#> 82.1 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 103.1 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 53.1 24.00 0 32 0 1
#> 33.1 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 148.1 24.00 0 61 1 0
#> 87.1 24.00 0 27 0 0
#> 95 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#> 191 24.00 0 60 0 1
#> 118.1 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 148.2 24.00 0 61 1 0
#> 67.1 24.00 0 25 0 0
#> 138.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 103.2 24.00 0 56 1 0
#> 109.1 24.00 0 48 0 0
#> 87.2 24.00 0 27 0 0
#> 135.1 24.00 0 58 1 0
#> 174.1 24.00 0 49 1 0
#> 141.2 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 148.3 24.00 0 61 1 0
#> 144 24.00 0 28 0 1
#> 27 24.00 0 63 1 0
#> 46 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 191.1 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 47.1 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 47.2 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 33.2 24.00 0 53 0 0
#> 141.3 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 162.1 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 118.2 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 27.2 24.00 0 63 1 0
#> 138.2 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 103.3 24.00 0 56 1 0
#> 19.1 24.00 0 57 0 1
#> 19.2 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 74 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 19.3 24.00 0 57 0 1
#> 27.3 24.00 0 63 1 0
#> 28.1 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0992 NA NA NA
#> 2 age, Cure model -0.00168 NA NA NA
#> 3 grade_ii, Cure model -0.172 NA NA NA
#> 4 grade_iii, Cure model 1.28 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00439 NA NA NA
#> 2 grade_ii, Survival model 0.630 NA NA NA
#> 3 grade_iii, Survival model 0.566 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.09916 -0.00168 -0.17206 1.27894
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 242.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.099164180 -0.001680121 -0.172055086 1.278939420
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004386588 0.630176104 0.566364964
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.829153856 0.655426931 0.023153127 0.491848716 0.423349492 0.722539610
#> [7] 0.664153503 0.916750227 0.392894902 0.646645537 0.154184463 0.730844472
#> [13] 0.620147435 0.501575761 0.203977567 0.557580701 0.901008113 0.129216005
#> [19] 0.320372200 0.203977567 0.203977567 0.821101980 0.382437128 0.584334657
#> [25] 0.298046671 0.423349492 0.672821454 0.372024142 0.829153856 0.916750227
#> [31] 0.482166630 0.501575761 0.320372200 0.705951365 0.962449693 0.403245184
#> [37] 0.462707599 0.947141694 0.548346263 0.805011071 0.443001602 0.916750227
#> [43] 0.203977567 0.916750227 0.403245184 0.672821454 0.602276290 0.672821454
#> [49] 0.954814644 0.043563263 0.007104593 0.730844472 0.620147435 0.264048483
#> [55] 0.520467841 0.179922251 0.077989632 0.772186815 0.179922251 0.861300833
#> [61] 0.539041909 0.251474704 0.593335305 0.264048483 0.116559226 0.885231688
#> [67] 0.705951365 0.755687372 0.061916000 0.557580701 0.977575991 0.672821454
#> [73] 0.341807500 0.962449693 0.341807500 0.747411712 0.341807500 0.908902558
#> [79] 0.129216005 0.829153856 0.796849179 0.102961247 0.298046671 0.977575991
#> [85] 0.861300833 0.077989632 0.637804367 0.264048483 0.602276290 0.520467841
#> [91] 0.780488931 0.805011071 0.977575991 0.472408081 0.557580701 0.755687372
#> [97] 0.877250507 0.780488931 0.452889403 0.885231688 0.154184463 0.853236491
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 56 167 168 23 108 13 18 187 76 39 169 81 26
#> 12.21 15.55 23.72 16.92 18.29 14.34 15.21 9.92 19.22 15.59 22.41 14.06 15.77
#> 106 66 192 145 15 32 66.1 66.2 42 58 5 99 108.1
#> 16.67 22.13 16.44 10.07 22.68 20.90 22.13 22.13 12.43 19.34 16.43 21.19 18.29
#> 96 166 56.1 187.1 45 106.1 32.1 57 91 97 117 16 181
#> 14.54 19.98 12.21 9.92 17.42 16.67 20.90 14.46 5.33 19.14 17.46 8.71 16.46
#> 37 51 187.2 66.3 187.3 97.1 96.1 100 96.2 25 164 24 81.1
#> 12.52 18.23 9.92 22.13 9.92 19.14 14.54 16.07 14.54 6.32 23.60 23.89 14.06
#> 26.1 139 171 194 92 14 194.1 43 130 197 188 139.1 63
#> 15.77 21.49 16.57 22.40 22.92 12.89 22.40 12.10 16.47 21.60 16.16 21.49 22.77
#> 52 57.1 155 129 85 127 96.3 128 91.1 128.1 60 128.2 101
#> 10.42 14.46 13.08 23.41 16.44 3.53 14.54 20.35 5.33 20.35 13.15 20.35 9.97
#> 15.1 56.2 154 113 36 127.1 43.1 92.1 125 139.2 100.1 171.1 140
#> 22.68 12.21 12.63 22.86 21.19 3.53 12.10 22.92 15.65 21.49 16.07 16.57 12.68
#> 37.1 127.2 30 192.1 155.1 159 140.1 110 52.1 169.1 49 161 118
#> 12.52 3.53 17.43 16.44 13.08 10.55 12.68 17.56 10.42 22.41 12.19 24.00 24.00
#> 138 103 147 67 82 121 47 119 148 156 172 121.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 53 54 185 44 141.1 82.1 162 103.1 80 33 53.1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 143 11 148.1 87.1 95 146 54.1 191 118.1 185.1 135 148.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 138.1 174 186 109 20 103.2 109.1 87.2 135.1 174.1 141.2 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.3 144 27 46 102 191.1 19 47.1 163 47.2 83 33.2 141.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 162.1 27.1 118.2 1 27.2 138.2 35 28 131 62 103.3 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.2 196 74 151 19.3 27.3 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002044053 0.406759465 0.262490506
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.78542945 0.01238531 -0.07389813
#> grade_iii, Cure model
#> 1.13963215
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 123 13.00 1 44 1 0
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 14 12.89 1 21 0 0
#> 177 12.53 1 75 0 0
#> 192 16.44 1 31 1 0
#> 150 20.33 1 48 0 0
#> 154 12.63 1 20 1 0
#> 91 5.33 1 61 0 1
#> 36 21.19 1 48 0 1
#> 171 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 59.1 10.16 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 166 19.98 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 197 21.60 1 69 1 0
#> 155 13.08 1 26 0 0
#> 123.1 13.00 1 44 1 0
#> 97 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 37 12.52 1 57 1 0
#> 106 16.67 1 49 1 0
#> 30 17.43 1 78 0 0
#> 177.1 12.53 1 75 0 0
#> 97.1 19.14 1 65 0 1
#> 175 21.91 1 43 0 0
#> 91.2 5.33 1 61 0 1
#> 99 21.19 1 38 0 1
#> 192.1 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 59.2 10.16 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 110 17.56 1 65 0 1
#> 113 22.86 1 34 0 0
#> 5 16.43 1 51 0 1
#> 124 9.73 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 91.3 5.33 1 61 0 1
#> 39 15.59 1 37 0 1
#> 13.1 14.34 1 54 0 1
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 92 22.92 1 47 0 1
#> 13.2 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 69 23.23 1 25 0 1
#> 59.3 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 41 18.02 1 40 1 0
#> 150.1 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 56 12.21 1 60 0 0
#> 107 11.18 1 54 1 0
#> 127 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 117.1 17.46 1 26 0 1
#> 168 23.72 1 70 0 0
#> 127.1 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 61.1 10.12 1 36 0 1
#> 26 15.77 1 49 0 1
#> 32.1 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 60 13.15 1 38 1 0
#> 99.1 21.19 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 107.1 11.18 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 91.4 5.33 1 61 0 1
#> 91.5 5.33 1 61 0 1
#> 133 14.65 1 57 0 0
#> 68.1 20.62 1 44 0 0
#> 81 14.06 1 34 0 0
#> 170.1 19.54 1 43 0 1
#> 129.1 23.41 1 53 1 0
#> 96.1 14.54 1 33 0 1
#> 105.1 19.75 1 60 0 0
#> 107.2 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 100.1 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 164.1 23.60 1 76 0 1
#> 90.1 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 171.1 16.57 1 41 0 1
#> 180 14.82 1 37 0 0
#> 41.1 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 107.3 11.18 1 54 1 0
#> 77 7.27 1 67 0 1
#> 29.1 15.45 1 68 1 0
#> 36.1 21.19 1 48 0 1
#> 39.1 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 52.2 10.42 1 52 0 1
#> 66 22.13 1 53 0 0
#> 66.1 22.13 1 53 0 0
#> 45.1 17.42 1 54 0 1
#> 104 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 98.1 24.00 0 34 1 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 162.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 103.1 24.00 0 56 1 0
#> 185 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 162.2 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 3 24.00 0 31 1 0
#> 103.2 24.00 0 56 1 0
#> 84 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 103.3 24.00 0 56 1 0
#> 138 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 104.1 24.00 0 50 1 0
#> 116.1 24.00 0 58 0 1
#> 104.2 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 71.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 143 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 109 24.00 0 48 0 0
#> 84.2 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 44.2 24.00 0 56 0 0
#> 21.1 24.00 0 47 0 0
#> 138.1 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 38 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 142 24.00 0 53 0 0
#> 98.3 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 71.2 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 22.1 24.00 0 52 1 0
#> 116.2 24.00 0 58 0 1
#> 94.1 24.00 0 51 0 1
#> 33.1 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 33.2 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 35.1 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 33.3 24.00 0 53 0 0
#> 162.3 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 178.1 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 121 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 162.4 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 122.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 21.2 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 31.1 24.00 0 36 0 1
#> 160.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 160.2 24.00 0 31 1 0
#> 17.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.785 NA NA NA
#> 2 age, Cure model 0.0124 NA NA NA
#> 3 grade_ii, Cure model -0.0739 NA NA NA
#> 4 grade_iii, Cure model 1.14 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00204 NA NA NA
#> 2 grade_ii, Survival model 0.407 NA NA NA
#> 3 grade_iii, Survival model 0.262 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.78543 0.01239 -0.07390 1.13963
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 245.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.78542945 0.01238531 -0.07389813 1.13963215
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002044053 0.406759465 0.262490506
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.210939465 0.742301423 0.570231064 0.260924998 0.688707415 0.759971456
#> [7] 0.777708960 0.533564929 0.320158650 0.768862804 0.933404255 0.221824218
#> [13] 0.514893987 0.924851256 0.144016078 0.339907944 0.933404255 0.369900254
#> [19] 0.199859210 0.733333147 0.742301423 0.389639737 0.873511464 0.873511464
#> [25] 0.795357404 0.505404412 0.476857587 0.777708960 0.389639737 0.177189054
#> [31] 0.933404255 0.221824218 0.533564929 0.899155821 0.076481276 0.051957123
#> [37] 0.438482831 0.121304179 0.560969550 0.467266543 0.448211248 0.280997296
#> [43] 0.933404255 0.607164408 0.688707415 0.022881093 0.670704210 0.821866688
#> [49] 0.132614420 0.110064999 0.688707415 0.643393427 0.098615346 0.597940489
#> [55] 0.419183258 0.320158650 0.486477151 0.804197913 0.830669770 0.983166568
#> [61] 0.300522900 0.448211248 0.037005358 0.983166568 0.188588991 0.899155821
#> [67] 0.588672294 0.280997296 0.349958063 0.724370546 0.221824218 0.830669770
#> [73] 0.864834828 0.933404255 0.933404255 0.661588339 0.300522900 0.715364522
#> [79] 0.369900254 0.076481276 0.670704210 0.349958063 0.830669770 0.007764334
#> [85] 0.813049654 0.570231064 0.409242016 0.051957123 0.260924998 0.625359446
#> [91] 0.514893987 0.652486262 0.419183258 0.830669770 0.916266413 0.625359446
#> [97] 0.221824218 0.607164408 0.533564929 0.873511464 0.155237939 0.155237939
#> [103] 0.486477151 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 153 123 100 90 13 14 177 192 150 154 91 36 171
#> 21.33 13.00 16.07 20.94 14.34 12.89 12.53 16.44 20.33 12.63 5.33 21.19 16.57
#> 25 194 166 91.1 170 197 155 123.1 97 52 52.1 37 106
#> 6.32 22.40 19.98 5.33 19.54 21.60 13.08 13.00 19.14 10.42 10.42 12.52 16.67
#> 30 177.1 97.1 175 91.2 99 192.1 61 129 164 110 113 5
#> 17.43 12.53 19.14 21.91 5.33 21.19 16.44 10.12 23.41 23.60 17.56 22.86 16.43
#> 111 117 32 91.3 39 13.1 86 96 43 15 92 13.2 157
#> 17.45 17.46 20.90 5.33 15.59 14.34 23.81 14.54 12.10 22.68 22.92 14.34 15.10
#> 69 125 41 150.1 45 56 107 127 68 117.1 168 127.1 136
#> 23.23 15.65 18.02 20.33 17.42 12.21 11.18 3.53 20.62 17.46 23.72 3.53 21.83
#> 61.1 26 32.1 105 60 99.1 107.1 10 91.4 91.5 133 68.1 81
#> 10.12 15.77 20.90 19.75 13.15 21.19 11.18 10.53 5.33 5.33 14.65 20.62 14.06
#> 170.1 129.1 96.1 105.1 107.2 24 49 100.1 179 164.1 90.1 29 171.1
#> 19.54 23.41 14.54 19.75 11.18 23.89 12.19 16.07 18.63 23.60 20.94 15.45 16.57
#> 180 41.1 107.3 77 29.1 36.1 39.1 85 52.2 66 66.1 45.1 104
#> 14.82 18.02 11.18 7.27 15.45 21.19 15.59 16.44 10.42 22.13 22.13 17.42 24.00
#> 98 98.1 162 21 44 193 103 162.1 17 27 103.1 185 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.2 47 148 3 103.2 84 191 116 94 103.3 138 44.1 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 104.2 71 22 17.1 156 84.1 71.1 160 98.2 143 122 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 35 109 84.2 20 44.2 21.1 138.1 1 38 33 144 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.3 72 71.2 65 22.1 116.2 94.1 33.1 163 33.2 131 75 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 33.3 162.3 72.1 178.1 46 147 121 46.1 162.4 31 122.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 135 31.1 160.1 87 160.2 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001110667 0.556745959 0.591762820
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.286857851 0.004737612 -0.017758526
#> grade_iii, Cure model
#> 0.841796916
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 108 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 85 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 56 12.21 1 60 0 0
#> 168 23.72 1 70 0 0
#> 154 12.63 1 20 1 0
#> 128 20.35 1 35 0 1
#> 177 12.53 1 75 0 0
#> 111 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 60 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 189 10.51 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 158 20.14 1 74 1 0
#> 58 19.34 1 39 0 0
#> 166 19.98 1 48 0 0
#> 14 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 190 20.81 1 42 1 0
#> 61.1 10.12 1 36 0 1
#> 128.1 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 177.1 12.53 1 75 0 0
#> 166.2 19.98 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 6 15.64 1 39 0 0
#> 41 18.02 1 40 1 0
#> 125.1 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 68 20.62 1 44 0 0
#> 111.1 17.45 1 47 0 1
#> 167 15.55 1 56 1 0
#> 59 10.16 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 93 10.33 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 129 23.41 1 53 1 0
#> 188 16.16 1 46 0 1
#> 189.1 10.51 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 171 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 167.1 15.55 1 56 1 0
#> 153 21.33 1 55 1 0
#> 76.1 19.22 1 54 0 1
#> 56.2 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 187 9.92 1 39 1 0
#> 181 16.46 1 45 0 1
#> 88.1 18.37 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 195.1 11.76 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 56.3 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 45 17.42 1 54 0 1
#> 175 21.91 1 43 0 0
#> 175.1 21.91 1 43 0 0
#> 77.1 7.27 1 67 0 1
#> 188.1 16.16 1 46 0 1
#> 15.1 22.68 1 48 0 0
#> 181.2 16.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 58.2 19.34 1 39 0 0
#> 130 16.47 1 53 0 1
#> 58.3 19.34 1 39 0 0
#> 52 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 81 14.06 1 34 0 0
#> 170 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 40 18.00 1 28 1 0
#> 25.1 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 39 15.59 1 37 0 1
#> 175.2 21.91 1 43 0 0
#> 158.1 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 40.1 18.00 1 28 1 0
#> 169 22.41 1 46 0 0
#> 59.1 10.16 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 24.1 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 166.3 19.98 1 48 0 0
#> 128.2 20.35 1 35 0 1
#> 127 3.53 1 62 0 1
#> 166.4 19.98 1 48 0 0
#> 24.2 23.89 1 38 0 0
#> 134 17.81 1 47 1 0
#> 105 19.75 1 60 0 0
#> 63 22.77 1 31 1 0
#> 36.1 21.19 1 48 0 1
#> 127.1 3.53 1 62 0 1
#> 189.2 10.51 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 191 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 191.1 24.00 0 60 0 1
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 185 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 80 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 54 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 112 24.00 0 61 0 0
#> 173.1 24.00 0 19 0 1
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 54.1 24.00 0 53 1 0
#> 87.1 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 119.1 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 138.1 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 126.1 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 64.1 24.00 0 43 0 0
#> 19.1 24.00 0 57 0 1
#> 178 24.00 0 52 1 0
#> 165.1 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 132.1 24.00 0 55 0 0
#> 191.2 24.00 0 60 0 1
#> 62.1 24.00 0 71 0 0
#> 62.2 24.00 0 71 0 0
#> 72.1 24.00 0 40 0 1
#> 200.1 24.00 0 64 0 0
#> 143 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 35 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 83 24.00 0 6 0 0
#> 112.1 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 44.1 24.00 0 56 0 0
#> 185.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 9.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 95.1 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 65 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 1 24.00 0 23 1 0
#> 161.1 24.00 0 45 0 0
#> 83.1 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 9.2 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 21.2 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 118 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 67.1 24.00 0 25 0 0
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.287 NA NA NA
#> 2 age, Cure model 0.00474 NA NA NA
#> 3 grade_ii, Cure model -0.0178 NA NA NA
#> 4 grade_iii, Cure model 0.842 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00111 NA NA NA
#> 2 grade_ii, Survival model 0.557 NA NA NA
#> 3 grade_iii, Survival model 0.592 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.286858 0.004738 -0.017759 0.841797
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 257.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.286857851 0.004737612 -0.017758526 0.841796916
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001110667 0.556745959 0.591762820
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.27220987 0.24883820 0.51971145 0.60996407 0.67732421 0.46242152
#> [7] 0.90054427 0.85582489 0.08076057 0.83332418 0.30637966 0.84083970
#> [13] 0.59269665 0.94410528 0.81070424 0.13186046 0.93691343 0.33666957
#> [19] 0.42412087 0.35644733 0.81826538 0.70975591 0.28379718 0.90054427
#> [25] 0.30637966 0.78795496 0.35644733 0.95828616 0.84083970 0.35644733
#> [31] 0.85582489 0.72564129 0.53859797 0.70975591 0.09966477 0.29507809
#> [37] 0.59269665 0.74927648 0.42412087 0.89309400 0.76471508 0.11647603
#> [43] 0.68555941 0.78795496 0.63591952 0.02191654 0.50063701 0.74927648
#> [49] 0.23598283 0.46242152 0.85582489 0.15925679 0.92968373 0.65292925
#> [55] 0.50063701 0.81826538 0.65292925 0.85582489 0.58381265 0.94410528
#> [61] 0.61867007 0.19823427 0.19823427 0.95828616 0.68555941 0.15925679
#> [67] 0.65292925 0.49102603 0.57483559 0.42412087 0.64446388 0.42412087
#> [73] 0.88559962 0.77247691 0.80309535 0.41424302 0.70165526 0.48142162
#> [79] 0.78024354 0.97232627 0.54787839 0.97232627 0.06219969 0.73363166
#> [85] 0.19823427 0.33666957 0.52920930 0.54787839 0.18489098 0.73363166
#> [91] 0.02191654 0.62729091 0.91520528 0.35644733 0.30637966 0.98622981
#> [97] 0.35644733 0.02191654 0.56586432 0.40419193 0.14599816 0.24883820
#> [103] 0.98622981 0.91520528 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 90 36 108 30 85 76 61 56 168 154 128 177 111
#> 20.94 21.19 18.29 17.43 16.44 19.22 10.12 12.21 23.72 12.63 20.35 12.53 17.45
#> 70 60 69 149 158 58 166 14 125 190 61.1 128.1 13
#> 7.38 13.15 23.23 8.37 20.14 19.34 19.98 12.89 15.65 20.81 10.12 20.35 14.34
#> 166.1 77 177.1 166.2 56.1 6 41 125.1 164 68 111.1 167 58.1
#> 19.98 7.27 12.53 19.98 12.21 15.64 18.02 15.65 23.60 20.62 17.45 15.55 19.34
#> 93 180 129 188 13.1 171 24 88 167.1 153 76.1 56.2 15
#> 10.33 14.82 23.41 16.16 14.34 16.57 23.89 18.37 15.55 21.33 19.22 12.21 22.68
#> 187 181 88.1 14.1 181.1 56.3 110 70.1 45 175 175.1 77.1 188.1
#> 9.92 16.46 18.37 12.89 16.46 12.21 17.56 7.38 17.42 21.91 21.91 7.27 16.16
#> 15.1 181.2 8 184 58.2 130 58.3 52 133 81 170 100 179
#> 22.68 16.46 18.43 17.77 19.34 16.47 19.34 10.42 14.65 14.06 19.54 16.07 18.63
#> 57 25 40 25.1 78 39 175.2 158.1 51 40.1 169 39.1 24.1
#> 14.46 6.32 18.00 6.32 23.88 15.59 21.91 20.14 18.23 18.00 22.41 15.59 23.89
#> 23 101 166.3 128.2 127 166.4 24.2 134 105 63 36.1 127.1 101.1
#> 16.92 9.97 19.98 20.35 3.53 19.98 23.89 17.81 19.75 22.77 21.19 3.53 9.97
#> 191 126 122 21 191.1 119 82 185 104 132 67 173 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 54 87 112 173.1 9 46 95 62 54.1 87.1 17 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 138 186 138.1 19 165 12 176 126.1 64 64.1 19.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 21.1 72 200 132.1 191.2 62.1 62.2 72.1 200.1 143 178.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 27 161 83 112.1 20 44 74 44.1 185.1 146 31 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 95.1 2 65 151 1 161.1 83.1 47 80.1 172 9.2 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 196 21.2 71 53 118 46.1 147 67.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01185135 0.77483158 0.31000624
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.92640634 0.01265268 0.37225614
#> grade_iii, Cure model
#> 1.12563223
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 167 15.55 1 56 1 0
#> 194 22.40 1 38 0 1
#> 45 17.42 1 54 0 1
#> 52 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 91 5.33 1 61 0 1
#> 90 20.94 1 50 0 1
#> 52.1 10.42 1 52 0 1
#> 90.1 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 70 7.38 1 30 1 0
#> 63 22.77 1 31 1 0
#> 145 10.07 1 65 1 0
#> 130 16.47 1 53 0 1
#> 58 19.34 1 39 0 0
#> 37 12.52 1 57 1 0
#> 130.1 16.47 1 53 0 1
#> 25 6.32 1 34 1 0
#> 168 23.72 1 70 0 0
#> 107 11.18 1 54 1 0
#> 90.2 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 90.3 20.94 1 50 0 1
#> 130.2 16.47 1 53 0 1
#> 136.1 21.83 1 43 0 1
#> 111 17.45 1 47 0 1
#> 158 20.14 1 74 1 0
#> 76 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 40 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 110 17.56 1 65 0 1
#> 96 14.54 1 33 0 1
#> 70.1 7.38 1 30 1 0
#> 5.1 16.43 1 51 0 1
#> 36.1 21.19 1 48 0 1
#> 32 20.90 1 37 1 0
#> 111.1 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 140 12.68 1 59 1 0
#> 30 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 43 12.10 1 61 0 1
#> 52.2 10.42 1 52 0 1
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 167.1 15.55 1 56 1 0
#> 154.1 12.63 1 20 1 0
#> 111.2 17.45 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 61 10.12 1 36 0 1
#> 187 9.92 1 39 1 0
#> 58.1 19.34 1 39 0 0
#> 180 14.82 1 37 0 0
#> 107.1 11.18 1 54 1 0
#> 149 8.37 1 33 1 0
#> 51 18.23 1 83 0 1
#> 171 16.57 1 41 0 1
#> 55 19.34 1 69 0 1
#> 195.1 11.76 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 24 23.89 1 38 0 0
#> 90.4 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 10.1 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 189 10.51 1 NA 1 0
#> 167.2 15.55 1 56 1 0
#> 125.1 15.65 1 67 1 0
#> 70.2 7.38 1 30 1 0
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 179.1 18.63 1 42 0 0
#> 59.1 10.16 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 79 16.23 1 54 1 0
#> 76.1 19.22 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 92 22.92 1 47 0 1
#> 100 16.07 1 60 0 0
#> 55.1 19.34 1 69 0 1
#> 181 16.46 1 45 0 1
#> 140.1 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 77.1 7.27 1 67 0 1
#> 96.1 14.54 1 33 0 1
#> 76.2 19.22 1 54 0 1
#> 14 12.89 1 21 0 0
#> 179.2 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 133 14.65 1 57 0 0
#> 61.1 10.12 1 36 0 1
#> 192.1 16.44 1 31 1 0
#> 13.1 14.34 1 54 0 1
#> 16 8.71 1 71 0 1
#> 171.1 16.57 1 41 0 1
#> 190.1 20.81 1 42 1 0
#> 136.2 21.83 1 43 0 1
#> 134.1 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 8 18.43 1 32 0 0
#> 16.1 8.71 1 71 0 1
#> 134.2 17.81 1 47 1 0
#> 49 12.19 1 48 1 0
#> 93 10.33 1 52 0 1
#> 196 24.00 0 19 0 0
#> 82 24.00 0 34 0 0
#> 152 24.00 0 36 0 1
#> 144 24.00 0 28 0 1
#> 104 24.00 0 50 1 0
#> 196.1 24.00 0 19 0 0
#> 135 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 54.1 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 196.2 24.00 0 19 0 0
#> 147 24.00 0 76 1 0
#> 198 24.00 0 66 0 1
#> 152.1 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 27 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 121 24.00 0 57 1 0
#> 1.1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 17 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 98 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 64 24.00 0 43 0 0
#> 121.1 24.00 0 57 1 0
#> 17.1 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 176 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 144.1 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 19 24.00 0 57 0 1
#> 47 24.00 0 38 0 1
#> 185.1 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 176.1 24.00 0 43 0 1
#> 102.1 24.00 0 49 0 0
#> 176.2 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 102.2 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 160.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 126.1 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 131.1 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 17.3 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 191.1 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 118.1 24.00 0 44 1 0
#> 135.2 24.00 0 58 1 0
#> 95 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.926 NA NA NA
#> 2 age, Cure model 0.0127 NA NA NA
#> 3 grade_ii, Cure model 0.372 NA NA NA
#> 4 grade_iii, Cure model 1.13 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0119 NA NA NA
#> 2 grade_ii, Survival model 0.775 NA NA NA
#> 3 grade_iii, Survival model 0.310 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.92641 0.01265 0.37226 1.12563
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.92640634 0.01265268 0.37225614 1.12563223
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01185135 0.77483158 0.31000624
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7265203 0.8208788 0.3569749 0.7203123 0.9286164 0.3773883 0.9933178
#> [8] 0.4681462 0.9286164 0.4681462 0.8056930 0.9728595 0.2907538 0.9512686
#> [15] 0.7446810 0.5649083 0.9009632 0.7446810 0.9899458 0.2127838 0.9130916
#> [22] 0.4681462 0.4259336 0.5355521 0.8926835 0.4681462 0.7446810 0.3773883
#> [29] 0.6950504 0.5555400 0.5985489 0.7842552 0.6609492 0.8395526 0.6223584
#> [36] 0.6884172 0.8532841 0.9728595 0.7842552 0.4259336 0.5243815 0.6950504
#> [43] 0.8711216 0.8842671 0.7140183 0.4259336 0.9090875 0.9286164 0.9831615
#> [50] 0.8109285 0.8208788 0.8926835 0.6950504 0.9208702 0.9437795 0.9549667
#> [57] 0.5649083 0.8441469 0.9130916 0.9693348 0.6533913 0.7326725 0.5649083
#> [64] 0.6683362 0.1124909 0.4681462 0.8349396 0.9208702 0.7677234 0.8208788
#> [71] 0.8109285 0.9728595 0.7677234 0.8622760 0.6223584 0.9586302 0.3351401
#> [78] 0.7950871 0.5985489 0.2907538 0.2558099 0.8004083 0.5649083 0.7619732
#> [85] 0.8842671 0.9966692 0.9831615 0.8532841 0.5985489 0.8799088 0.6223584
#> [92] 0.8755445 0.8487273 0.9437795 0.7677234 0.8622760 0.9622412 0.7326725
#> [99] 0.5355521 0.3773883 0.6683362 0.1124909 0.6455947 0.9622412 0.6683362
#> [106] 0.9050512 0.9399947 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 23 167 194 45 52 136 91 90 52.1 90.1 26 70 63
#> 16.92 15.55 22.40 17.42 10.42 21.83 5.33 20.94 10.42 20.94 15.77 7.38 22.77
#> 145 130 58 37 130.1 25 168 107 90.2 36 190 154 90.3
#> 10.07 16.47 19.34 12.52 16.47 6.32 23.72 11.18 20.94 21.19 20.81 12.63 20.94
#> 130.2 136.1 111 158 76 5 40 157 179 110 96 70.1 5.1
#> 16.47 21.83 17.45 20.14 19.22 16.43 18.00 15.10 18.63 17.56 14.54 7.38 16.43
#> 36.1 32 111.1 81 140 30 99 43 52.2 77 125 167.1 154.1
#> 21.19 20.90 17.45 14.06 12.68 17.43 21.19 12.10 10.42 7.27 15.65 15.55 12.63
#> 111.2 10 61 187 58.1 180 107.1 149 51 171 55 134 24
#> 17.45 10.53 10.12 9.92 19.34 14.82 11.18 8.37 18.23 16.57 19.34 17.81 23.89
#> 90.4 29 10.1 85 167.2 125.1 70.2 192 13 179.1 183 15 79
#> 20.94 15.45 10.53 16.44 15.55 15.65 7.38 16.44 14.34 18.63 9.24 22.68 16.23
#> 76.1 63.1 92 100 55.1 181 140.1 127 77.1 96.1 76.2 14 179.2
#> 19.22 22.77 22.92 16.07 19.34 16.46 12.68 3.53 7.27 14.54 19.22 12.89 18.63
#> 123 133 61.1 192.1 13.1 16 171.1 190.1 136.2 134.1 24.1 8 16.1
#> 13.00 14.65 10.12 16.44 14.34 8.71 16.57 20.81 21.83 17.81 23.89 18.43 8.71
#> 134.2 49 93 196 82 152 144 104 196.1 135 72 54 9
#> 17.81 12.19 10.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 54.1 102 28 1 185 196.2 147 198 152.1 7 163 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 20 21 165 186 3 193 126 112 121 1.1 151 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 71 141 46 156 98 131 87 64 121.1 17.1 191 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 22 178 144.1 160 83 119 19 47 185.1 17.2 118 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 176.2 146 102.2 172 165.1 160.1 38 112.1 126.1 198.1 131.1 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.3 64.1 191.1 173 162 135.1 118.1 135.2 95 138 138.1 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0001155206 0.2318931022 0.7294684224
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05888704 0.01647281 0.40737716
#> grade_iii, Cure model
#> 1.00484160
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 5 16.43 1 51 0 1
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 49 12.19 1 48 1 0
#> 45 17.42 1 54 0 1
#> 39 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 40.1 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 106 16.67 1 49 1 0
#> 39.1 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 127 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 106.1 16.67 1 49 1 0
#> 91 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 96 14.54 1 33 0 1
#> 78 23.88 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 61 10.12 1 36 0 1
#> 127.1 3.53 1 62 0 1
#> 59 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 88 18.37 1 47 0 0
#> 158 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 96.1 14.54 1 33 0 1
#> 100 16.07 1 60 0 0
#> 66 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 117 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 127.2 3.53 1 62 0 1
#> 37 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 97 19.14 1 65 0 1
#> 133 14.65 1 57 0 0
#> 136 21.83 1 43 0 1
#> 77.1 7.27 1 67 0 1
#> 13.2 14.34 1 54 0 1
#> 90 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 30 17.43 1 78 0 0
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 41.1 18.02 1 40 1 0
#> 52 10.42 1 52 0 1
#> 88.1 18.37 1 47 0 0
#> 149 8.37 1 33 1 0
#> 127.3 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 51 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 153 21.33 1 55 1 0
#> 85 16.44 1 36 0 0
#> 30.1 17.43 1 78 0 0
#> 32 20.90 1 37 1 0
#> 77.2 7.27 1 67 0 1
#> 145 10.07 1 65 1 0
#> 175 21.91 1 43 0 0
#> 167 15.55 1 56 1 0
#> 195.1 11.76 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 85.1 16.44 1 36 0 0
#> 101.1 9.97 1 10 0 1
#> 197.1 21.60 1 69 1 0
#> 192 16.44 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 159 10.55 1 50 0 1
#> 167.1 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 85.2 16.44 1 36 0 0
#> 5.1 16.43 1 51 0 1
#> 125 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 157 15.10 1 47 0 0
#> 61.1 10.12 1 36 0 1
#> 140 12.68 1 59 1 0
#> 192.1 16.44 1 31 1 0
#> 45.2 17.42 1 54 0 1
#> 77.3 7.27 1 67 0 1
#> 145.1 10.07 1 65 1 0
#> 4.1 17.64 1 NA 0 1
#> 100.1 16.07 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 133.1 14.65 1 57 0 0
#> 77.4 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 89 11.44 1 NA 0 0
#> 197.2 21.60 1 69 1 0
#> 175.1 21.91 1 43 0 0
#> 99.1 21.19 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 125.1 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 113 22.86 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 155 13.08 1 26 0 0
#> 40.2 18.00 1 28 1 0
#> 167.2 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 129 23.41 1 53 1 0
#> 48 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 176 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 176.1 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 144 24.00 0 28 0 1
#> 193 24.00 0 45 0 1
#> 12 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 146 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#> 74.2 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 75 24.00 0 21 1 0
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 48.1 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 122 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 46 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 71 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 46.1 24.00 0 71 0 0
#> 54.2 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 38.1 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 121 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 7 24.00 0 37 1 0
#> 198.1 24.00 0 66 0 1
#> 152 24.00 0 36 0 1
#> 34.2 24.00 0 36 0 0
#> 138.1 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 151.1 24.00 0 42 0 0
#> 22.1 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 143 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 72.2 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 176.2 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 146.1 24.00 0 63 1 0
#> 12.2 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 73.1 24.00 0 NA 0 1
#> 131.1 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 19 24.00 0 57 0 1
#> 109.2 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 73.2 24.00 0 NA 0 1
#> 191 24.00 0 60 0 1
#> 95 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0165 NA NA NA
#> 3 grade_ii, Cure model 0.407 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000116 NA NA NA
#> 2 grade_ii, Survival model 0.232 NA NA NA
#> 3 grade_iii, Survival model 0.729 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05889 0.01647 0.40738 1.00484
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05888704 0.01647281 0.40737716 1.00484160
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0001155206 0.2318931022 0.7294684224
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.93870691 0.61026884 0.78083728 0.78083728 0.85160423 0.51625662
#> [7] 0.69839508 0.41950615 0.41950615 0.63510468 0.54245786 0.69839508
#> [13] 0.04934819 0.97593673 0.35674944 0.54245786 0.96970008 0.90597292
#> [19] 0.75873269 0.01806401 0.91909648 0.87926170 0.97593673 0.51625662
#> [25] 0.36750531 0.31247034 0.92566983 0.75873269 0.65114744 0.12141923
#> [31] 0.44911354 0.25328503 0.81625030 0.84458649 0.46918849 0.87243456
#> [37] 0.97593673 0.83750626 0.30081672 0.33556508 0.74365742 0.17091171
#> [43] 0.93870691 0.78083728 0.27739300 0.66719294 0.49762628 0.32401627
#> [49] 0.39915531 0.55992517 0.39915531 0.86555025 0.36750531 0.93219421
#> [55] 0.97593673 0.18628716 0.47900228 0.38870922 0.33556508 0.22646291
#> [61] 0.56858331 0.49762628 0.28916544 0.93870691 0.89264244 0.13860295
#> [67] 0.71359089 0.45915053 0.56858331 0.90597292 0.18628716 0.56858331
#> [73] 0.22646291 0.85860731 0.71359089 0.77349528 0.56858331 0.61026884
#> [79] 0.68283878 0.47900228 0.73608221 0.87926170 0.83041087 0.56858331
#> [85] 0.51625662 0.93870691 0.89264244 0.65114744 0.81625030 0.74365742
#> [91] 0.93870691 0.80202858 0.18628716 0.13860295 0.25328503 0.63510468
#> [97] 0.68283878 0.62680781 0.08634200 0.66719294 0.80913935 0.41950615
#> [103] 0.71359089 0.10425438 0.06845761 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 77 5 13 13.1 49 45 39 40 40.1 188 106 39.1 86
#> 7.27 16.43 14.34 14.34 12.19 17.42 15.59 18.00 18.00 16.16 16.67 15.59 23.81
#> 127 179 106.1 91 101 96 78 187 61 127.1 45.1 88 158
#> 3.53 18.63 16.67 5.33 9.97 14.54 23.88 9.92 10.12 3.53 17.42 18.37 20.14
#> 16 96.1 100 66 134 99 14 42 117 93 127.2 37 68
#> 8.71 14.54 16.07 22.13 17.81 21.19 12.89 12.43 17.46 10.33 3.53 12.52 20.62
#> 97 133 136 77.1 13.2 90 26 30 105 41 181 41.1 52
#> 19.14 14.65 21.83 7.27 14.34 20.94 15.77 17.43 19.75 18.02 16.46 18.02 10.42
#> 88.1 149 127.3 197 111 51 97.1 153 85 30.1 32 77.2 145
#> 18.37 8.37 3.53 21.60 17.45 18.23 19.14 21.33 16.44 17.43 20.90 7.27 10.07
#> 175 167 184 85.1 101.1 197.1 192 153.1 159 167.1 57 85.2 5.1
#> 21.91 15.55 17.77 16.44 9.97 21.60 16.44 21.33 10.55 15.55 14.46 16.44 16.43
#> 125 111.1 157 61.1 140 192.1 45.2 77.3 145.1 100.1 14.1 133.1 77.4
#> 15.65 17.45 15.10 10.12 12.68 16.44 17.42 7.27 10.07 16.07 12.89 14.65 7.27
#> 60 197.2 175.1 99.1 188.1 125.1 79 113 26.1 155 40.2 167.2 63
#> 13.15 21.60 21.91 21.19 16.16 15.65 16.23 22.86 15.77 13.08 18.00 15.55 22.77
#> 129 48 54 22 138 64 176 74 198 176.1 74.1 27 80
#> 23.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 131 151 144 193 12 72 146 54.1 74.2 120 75 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 160 21 48.1 137 165 72.1 87 122 126 46 82 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 48.2 173 46.1 54.2 20 147 34 38.1 3 185 53 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 7 198.1 152 34.2 138.1 12.1 33 83 174 151.1 22.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 1 103 47 72.2 2 176.2 98 146.1 12.2 196 131.1 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 109.2 65 144.1 191 95 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002155759 0.568733778 0.330170796
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.73597815 0.01190433 0.46773749
#> grade_iii, Cure model
#> 0.62940245
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 55 19.34 1 69 0 1
#> 76 19.22 1 54 0 1
#> 166 19.98 1 48 0 0
#> 179 18.63 1 42 0 0
#> 171 16.57 1 41 0 1
#> 78 23.88 1 43 0 0
#> 16 8.71 1 71 0 1
#> 61 10.12 1 36 0 1
#> 108 18.29 1 39 0 1
#> 192 16.44 1 31 1 0
#> 183 9.24 1 67 1 0
#> 32 20.90 1 37 1 0
#> 108.1 18.29 1 39 0 1
#> 136 21.83 1 43 0 1
#> 187 9.92 1 39 1 0
#> 171.1 16.57 1 41 0 1
#> 13 14.34 1 54 0 1
#> 93 10.33 1 52 0 1
#> 145 10.07 1 65 1 0
#> 175 21.91 1 43 0 0
#> 16.1 8.71 1 71 0 1
#> 158 20.14 1 74 1 0
#> 175.1 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 180 14.82 1 37 0 0
#> 36 21.19 1 48 0 1
#> 164 23.60 1 76 0 1
#> 187.1 9.92 1 39 1 0
#> 18 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 68 20.62 1 44 0 0
#> 36.1 21.19 1 48 0 1
#> 134 17.81 1 47 1 0
#> 179.1 18.63 1 42 0 0
#> 66 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 30 17.43 1 78 0 0
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 192.1 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 105 19.75 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 6 15.64 1 39 0 0
#> 40 18.00 1 28 1 0
#> 107 11.18 1 54 1 0
#> 105.1 19.75 1 60 0 0
#> 41.1 18.02 1 40 1 0
#> 107.1 11.18 1 54 1 0
#> 30.2 17.43 1 78 0 0
#> 149 8.37 1 33 1 0
#> 70 7.38 1 30 1 0
#> 105.2 19.75 1 60 0 0
#> 171.2 16.57 1 41 0 1
#> 107.2 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 70.1 7.38 1 30 1 0
#> 108.2 18.29 1 39 0 1
#> 180.1 14.82 1 37 0 0
#> 10 10.53 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 24.1 23.89 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 180.2 14.82 1 37 0 0
#> 192.2 16.44 1 31 1 0
#> 77 7.27 1 67 0 1
#> 59 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 155 13.08 1 26 0 0
#> 86 23.81 1 58 0 1
#> 51.1 18.23 1 83 0 1
#> 195.1 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 195.2 11.76 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 158.1 20.14 1 74 1 0
#> 195.3 11.76 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 170.1 19.54 1 43 0 1
#> 171.3 16.57 1 41 0 1
#> 124 9.73 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 129.1 23.41 1 53 1 0
#> 13.1 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 195.4 11.76 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 107.3 11.18 1 54 1 0
#> 134.1 17.81 1 47 1 0
#> 85 16.44 1 36 0 0
#> 130 16.47 1 53 0 1
#> 30.3 17.43 1 78 0 0
#> 32.1 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 70.2 7.38 1 30 1 0
#> 187.2 9.92 1 39 1 0
#> 170.2 19.54 1 43 0 1
#> 106 16.67 1 49 1 0
#> 36.2 21.19 1 48 0 1
#> 16.2 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 45.1 17.42 1 54 0 1
#> 106.1 16.67 1 49 1 0
#> 81 14.06 1 34 0 0
#> 180.3 14.82 1 37 0 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 152 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 137 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 72 24.00 0 40 0 1
#> 73 24.00 0 NA 0 1
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 27 24.00 0 63 1 0
#> 178.1 24.00 0 52 1 0
#> 72.1 24.00 0 40 0 1
#> 131 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 48 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 191.1 24.00 0 60 0 1
#> 21 24.00 0 47 0 0
#> 141.1 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 84.1 24.00 0 39 0 1
#> 46.1 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 94 24.00 0 51 0 1
#> 20 24.00 0 46 1 0
#> 9.1 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 46.2 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 95 24.00 0 68 0 1
#> 152.1 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 3 24.00 0 31 1 0
#> 84.2 24.00 0 39 0 1
#> 138 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 64.1 24.00 0 43 0 0
#> 115 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 11.1 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 131.1 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 146.1 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 160.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 21.1 24.00 0 47 0 0
#> 152.2 24.00 0 36 0 1
#> 27.1 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 21.2 24.00 0 47 0 0
#> 186.1 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 80 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.736 NA NA NA
#> 2 age, Cure model 0.0119 NA NA NA
#> 3 grade_ii, Cure model 0.468 NA NA NA
#> 4 grade_iii, Cure model 0.629 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00216 NA NA NA
#> 2 grade_ii, Survival model 0.569 NA NA NA
#> 3 grade_iii, Survival model 0.330 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.7360 0.0119 0.4677 0.6294
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 256 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.73597815 0.01190433 0.46773749 0.62940245
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002155759 0.568733778 0.330170796
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.37934481 0.38934718 0.30969982 0.39928869 0.61292454 0.04001751
#> [7] 0.92214841 0.86581464 0.42856228 0.65627520 0.91416336 0.22552579
#> [13] 0.42856228 0.16612915 0.89030769 0.61292454 0.75774195 0.85754733
#> [19] 0.87405933 0.14049590 0.92214841 0.28965047 0.14049590 0.34997208
#> [25] 0.71559657 0.19177746 0.07396138 0.89030769 0.70707050 0.26887491
#> [31] 0.25803081 0.19177746 0.50462015 0.39928869 0.12726577 0.47651428
#> [37] 0.54103300 0.79158066 0.83277783 0.65627520 0.01351702 0.31992532
#> [43] 0.54103300 0.69848344 0.49527014 0.80008420 0.31992532 0.47651428
#> [49] 0.80008420 0.54103300 0.94577884 0.95367940 0.31992532 0.61292454
#> [55] 0.80008420 0.52275042 0.08976863 0.95367940 0.42856228 0.71559657
#> [61] 0.84105386 0.26887491 0.01351702 0.45728933 0.71559657 0.65627520
#> [67] 0.97681161 0.99229223 0.78309074 0.05753560 0.45728933 0.11418356
#> [73] 0.17920150 0.84105386 0.28965047 0.57698611 0.34997208 0.61292454
#> [79] 0.98457143 0.08976863 0.75774195 0.74921710 0.87405933 0.80008420
#> [85] 0.50462015 0.65627520 0.64748532 0.54103300 0.22552579 0.68990489
#> [91] 0.24722786 0.53190815 0.95367940 0.89030769 0.34997208 0.59511507
#> [97] 0.19177746 0.92214841 0.39928869 0.57698611 0.59511507 0.77460583
#> [103] 0.71559657 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 55 76 166 179 171 78 16 61 108 192 183 32 108.1
#> 19.34 19.22 19.98 18.63 16.57 23.88 8.71 10.12 18.29 16.44 9.24 20.90 18.29
#> 136 187 171.1 13 93 145 175 16.1 158 175.1 170 180 36
#> 21.83 9.92 16.57 14.34 10.33 10.07 21.91 8.71 20.14 21.91 19.54 14.82 21.19
#> 164 187.1 18 128 68 36.1 134 179.1 66 41 30 177 159
#> 23.60 9.92 15.21 20.35 20.62 21.19 17.81 18.63 22.13 18.02 17.43 12.53 10.55
#> 192.1 24 105 30.1 6 40 107 105.1 41.1 107.1 30.2 149 70
#> 16.44 23.89 19.75 17.43 15.64 18.00 11.18 19.75 18.02 11.18 17.43 8.37 7.38
#> 105.2 171.2 107.2 184 129 70.1 108.2 180.1 10 128.1 24.1 51 180.2
#> 19.75 16.57 11.18 17.77 23.41 7.38 18.29 14.82 10.53 20.35 23.89 18.23 14.82
#> 192.2 77 127 155 86 51.1 169 139 10.1 158.1 45 170.1 171.3
#> 16.44 7.27 3.53 13.08 23.81 18.23 22.41 21.49 10.53 20.14 17.42 19.54 16.57
#> 25 129.1 13.1 57 145.1 107.3 134.1 85 130 30.3 32.1 100 190
#> 6.32 23.41 14.34 14.46 10.07 11.18 17.81 16.44 16.47 17.43 20.90 16.07 20.81
#> 110 70.2 187.2 170.2 106 36.2 16.2 179.2 45.1 106.1 81 180.3 7
#> 17.56 7.38 9.92 19.54 16.67 21.19 8.71 18.63 17.42 16.67 14.06 14.82 24.00
#> 33 200 102 163 163.1 141 178 11 22 191 152 142 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 34 173 182 137 176 172 122.1 200.1 53 72 160 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 98 47 132 27 178.1 72.1 131 174.1 54 48 12 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 198 84 191.1 21 141.1 144 84.1 46.1 17 87.1 94 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 165 46.2 198.1 95 152.1 44 3 84.2 138 74 35 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 196 11.1 146 131.1 186 75 146.1 44.1 160.1 112 2 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.2 27.1 126 21.2 186.1 119 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01219993 0.67799819 0.65000651
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.07323047 -0.00376042 0.02908658
#> grade_iii, Cure model
#> 1.04776103
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 42 12.43 1 49 0 1
#> 139 21.49 1 63 1 0
#> 153 21.33 1 55 1 0
#> 154 12.63 1 20 1 0
#> 88 18.37 1 47 0 0
#> 96 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 39 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 97 19.14 1 65 0 1
#> 154.1 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 69 23.23 1 25 0 1
#> 139.1 21.49 1 63 1 0
#> 181 16.46 1 45 0 1
#> 159 10.55 1 50 0 1
#> 175 21.91 1 43 0 0
#> 45 17.42 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 66 22.13 1 53 0 0
#> 93 10.33 1 52 0 1
#> 42.1 12.43 1 49 0 1
#> 192 16.44 1 31 1 0
#> 188 16.16 1 46 0 1
#> 96.1 14.54 1 33 0 1
#> 164 23.60 1 76 0 1
#> 78 23.88 1 43 0 0
#> 18 15.21 1 49 1 0
#> 23 16.92 1 61 0 0
#> 81 14.06 1 34 0 0
#> 6 15.64 1 39 0 0
#> 130 16.47 1 53 0 1
#> 18.1 15.21 1 49 1 0
#> 145 10.07 1 65 1 0
#> 149 8.37 1 33 1 0
#> 187 9.92 1 39 1 0
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 157 15.10 1 47 0 0
#> 133 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 39.1 15.59 1 37 0 1
#> 106 16.67 1 49 1 0
#> 168 23.72 1 70 0 0
#> 158 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 10 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 56.1 12.21 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 110 17.56 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 39.2 15.59 1 37 0 1
#> 56.2 12.21 1 60 0 0
#> 30 17.43 1 78 0 0
#> 96.2 14.54 1 33 0 1
#> 59.1 10.16 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 179 18.63 1 42 0 0
#> 61.2 10.12 1 36 0 1
#> 76.1 19.22 1 54 0 1
#> 66.2 22.13 1 53 0 0
#> 101.1 9.97 1 10 0 1
#> 194.1 22.40 1 38 0 1
#> 52.2 10.42 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 45.1 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 184 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 134.1 17.81 1 47 1 0
#> 92 22.92 1 47 0 1
#> 6.1 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 114 13.68 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 139.2 21.49 1 63 1 0
#> 39.3 15.59 1 37 0 1
#> 49 12.19 1 48 1 0
#> 171.1 16.57 1 41 0 1
#> 49.1 12.19 1 48 1 0
#> 139.3 21.49 1 63 1 0
#> 194.2 22.40 1 38 0 1
#> 42.2 12.43 1 49 0 1
#> 159.1 10.55 1 50 0 1
#> 105.1 19.75 1 60 0 0
#> 170 19.54 1 43 0 1
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 8.2 18.43 1 32 0 0
#> 37 12.52 1 57 1 0
#> 96.3 14.54 1 33 0 1
#> 91 5.33 1 61 0 1
#> 181.1 16.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 81.1 14.06 1 34 0 0
#> 100 16.07 1 60 0 0
#> 197.1 21.60 1 69 1 0
#> 24.1 23.89 1 38 0 0
#> 160 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 82 24.00 0 34 0 0
#> 35.1 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 17 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 137.1 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 83 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 191 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 48.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 122.1 24.00 0 66 0 0
#> 122.2 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 198 24.00 0 66 0 1
#> 94.1 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 200.1 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 11 24.00 0 42 0 1
#> 200.2 24.00 0 64 0 0
#> 132.2 24.00 0 55 0 0
#> 126.1 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 138 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 33.1 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 1.1 24.00 0 23 1 0
#> 146 24.00 0 63 1 0
#> 137.2 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 33.2 24.00 0 53 0 0
#> 152.1 24.00 0 36 0 1
#> 126.2 24.00 0 48 0 0
#> 126.3 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 48.2 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 116.1 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 200.3 24.00 0 64 0 0
#> 200.4 24.00 0 64 0 0
#> 160.1 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 148 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 160.2 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 73.1 24.00 0 NA 0 1
#> 87.1 24.00 0 27 0 0
#> 116.2 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 186.2 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0732 NA NA NA
#> 2 age, Cure model -0.00376 NA NA NA
#> 3 grade_ii, Cure model 0.0291 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0122 NA NA NA
#> 2 grade_ii, Survival model 0.678 NA NA NA
#> 3 grade_iii, Survival model 0.650 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.07323 -0.00376 0.02909 1.04776
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.07323047 -0.00376042 0.02908658 1.04776103
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01219993 0.67799819 0.65000651
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.711440857 0.209734859 0.001482582 0.861024845 0.751297344 0.157161712
#> [7] 0.191377336 0.721553009 0.340661167 0.632006252 0.901176653 0.552158940
#> [13] 0.350725331 0.283261473 0.721553009 0.780723886 0.034940440 0.157161712
#> [19] 0.481377563 0.830824140 0.130362791 0.410345831 0.901176653 0.105791521
#> [25] 0.891054107 0.751297344 0.501461745 0.511535218 0.632006252 0.026168526
#> [31] 0.007268632 0.591600848 0.430441462 0.671293881 0.531747030 0.471182857
#> [37] 0.591600848 0.930971588 0.980340850 0.960726932 0.200570031 0.105791521
#> [43] 0.611605361 0.621763876 0.311713969 0.941022885 0.083677001 0.552158940
#> [49] 0.440737030 0.012480396 0.227828166 0.691437018 0.850890825 0.066821010
#> [55] 0.780723886 0.236900322 0.264807284 0.861024845 0.390163191 0.552158940
#> [61] 0.780723886 0.400176406 0.632006252 0.075039082 0.960726932 0.292685571
#> [67] 0.901176653 0.264807284 0.105791521 0.941022885 0.083677001 0.861024845
#> [73] 0.311713969 0.218828196 0.410345831 0.360675343 0.380184111 0.451012565
#> [79] 0.360675343 0.042902698 0.531747030 0.139377150 0.292685571 0.157161712
#> [85] 0.552158940 0.810737676 0.451012565 0.810737676 0.157161712 0.083677001
#> [91] 0.751297344 0.830824140 0.236900322 0.255419672 0.050753463 0.050753463
#> [97] 0.691437018 0.311713969 0.741336434 0.632006252 0.990166039 0.481377563
#> [103] 0.012480396 0.671293881 0.521590307 0.139377150 0.001482582 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 155 190 24 52 42 139 153 154 88 96 61 39 40
#> 13.08 20.81 23.89 10.42 12.43 21.49 21.33 12.63 18.37 14.54 10.12 15.59 18.00
#> 97 154.1 56 69 139.1 181 159 175 45 61.1 66 93 42.1
#> 19.14 12.63 12.21 23.23 21.49 16.46 10.55 21.91 17.42 10.12 22.13 10.33 12.43
#> 192 188 96.1 164 78 18 23 81 6 130 18.1 145 149
#> 16.44 16.16 14.54 23.60 23.88 15.21 16.92 14.06 15.64 16.47 15.21 10.07 8.37
#> 187 36 66.1 157 133 8 101 194 39.1 106 168 158 60
#> 9.92 21.19 22.13 15.10 14.65 18.43 9.97 22.40 15.59 16.67 23.72 20.14 13.15
#> 10 63 56.1 105 76 52.1 110 39.2 56.2 30 96.2 15 187.1
#> 10.53 22.77 12.21 19.75 19.22 10.42 17.56 15.59 12.21 17.43 14.54 22.68 9.92
#> 179 61.2 76.1 66.2 101.1 194.1 52.2 8.1 128 45.1 134 184 171
#> 18.63 10.12 19.22 22.13 9.97 22.40 10.42 18.43 20.35 17.42 17.81 17.77 16.57
#> 134.1 92 6.1 197 179.1 139.2 39.3 49 171.1 49.1 139.3 194.2 42.2
#> 17.81 22.92 15.64 21.60 18.63 21.49 15.59 12.19 16.57 12.19 21.49 22.40 12.43
#> 159.1 105.1 170 113 113.1 60.1 8.2 37 96.3 91 181.1 168.1 81.1
#> 10.55 19.75 19.54 22.86 22.86 13.15 18.43 12.52 14.54 5.33 16.46 23.72 14.06
#> 100 197.1 24.1 160 172 54 109 35 172.1 132 131 137 72
#> 16.07 21.60 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 35.1 48 200 17 33 144 31 2 102 28 137.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 131.1 47 186 103 83 122 38 7 191 94 48.1 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 122.1 122.2 152 182 198 94.1 1 46 200.1 165 9 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 186.1 98 11 200.2 132.2 126.1 196 138 27 33.1 19 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 137.2 95 33.2 152.1 126.2 126.3 174 48.2 116 116.1 12 200.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.4 160.1 28.1 148 151 160.2 165.1 87.1 116.2 21 186.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0002606304 0.7678177543 0.2595868583
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.70115379 0.01433034 -0.01348739
#> grade_iii, Cure model
#> 0.81878711
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 136 21.83 1 43 0 1
#> 140 12.68 1 59 1 0
#> 130 16.47 1 53 0 1
#> 56 12.21 1 60 0 0
#> 183 9.24 1 67 1 0
#> 68 20.62 1 44 0 0
#> 124 9.73 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 140.1 12.68 1 59 1 0
#> 130.1 16.47 1 53 0 1
#> 99 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 166 19.98 1 48 0 0
#> 99.1 21.19 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 25 6.32 1 34 1 0
#> 150 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 184.1 17.77 1 38 0 0
#> 96 14.54 1 33 0 1
#> 24.1 23.89 1 38 0 0
#> 130.2 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 179 18.63 1 42 0 0
#> 168 23.72 1 70 0 0
#> 6 15.64 1 39 0 0
#> 187 9.92 1 39 1 0
#> 192 16.44 1 31 1 0
#> 99.2 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 155 13.08 1 26 0 0
#> 187.1 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 180 14.82 1 37 0 0
#> 88.1 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 100 16.07 1 60 0 0
#> 57 14.46 1 45 0 1
#> 179.1 18.63 1 42 0 0
#> 26 15.77 1 49 0 1
#> 125.1 15.65 1 67 1 0
#> 77 7.27 1 67 0 1
#> 51 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 105 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 69.1 23.23 1 25 0 1
#> 177.1 12.53 1 75 0 0
#> 170 19.54 1 43 0 1
#> 51.1 18.23 1 83 0 1
#> 124.1 9.73 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 81.1 14.06 1 34 0 0
#> 128 20.35 1 35 0 1
#> 43 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 181 16.46 1 45 0 1
#> 125.2 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 76.1 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 179.2 18.63 1 42 0 0
#> 159 10.55 1 50 0 1
#> 101.1 9.97 1 10 0 1
#> 68.2 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 128.1 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 187.2 9.92 1 39 1 0
#> 150.1 20.33 1 48 0 0
#> 24.2 23.89 1 38 0 0
#> 170.1 19.54 1 43 0 1
#> 164 23.60 1 76 0 1
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 175 21.91 1 43 0 0
#> 45 17.42 1 54 0 1
#> 139 21.49 1 63 1 0
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 170.2 19.54 1 43 0 1
#> 56.1 12.21 1 60 0 0
#> 40 18.00 1 28 1 0
#> 99.3 21.19 1 38 0 1
#> 133.1 14.65 1 57 0 0
#> 133.2 14.65 1 57 0 0
#> 168.1 23.72 1 70 0 0
#> 81.2 14.06 1 34 0 0
#> 159.1 10.55 1 50 0 1
#> 24.3 23.89 1 38 0 0
#> 171 16.57 1 41 0 1
#> 40.1 18.00 1 28 1 0
#> 77.1 7.27 1 67 0 1
#> 145.1 10.07 1 65 1 0
#> 25.1 6.32 1 34 1 0
#> 39 15.59 1 37 0 1
#> 170.3 19.54 1 43 0 1
#> 180.1 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 57.1 14.46 1 45 0 1
#> 181.1 16.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 76.2 19.22 1 54 0 1
#> 62 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 147 24.00 0 76 1 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 186 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 161 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 144 24.00 0 28 0 1
#> 87 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 178 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 102 24.00 0 49 0 0
#> 75 24.00 0 21 1 0
#> 27.2 24.00 0 63 1 0
#> 182.1 24.00 0 35 0 0
#> 182.2 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 87.1 24.00 0 27 0 0
#> 109 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 104 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 67.1 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 87.2 24.00 0 27 0 0
#> 53 24.00 0 32 0 1
#> 84.1 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 137 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 84.2 24.00 0 39 0 1
#> 87.3 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 12.1 24.00 0 63 0 0
#> 142.2 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 185.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 33.2 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 109.2 24.00 0 48 0 0
#> 191.1 24.00 0 60 0 1
#> 191.2 24.00 0 60 0 1
#> 83.1 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 131 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 174.1 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 186.1 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 31.1 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 35.1 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 173.1 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.701 NA NA NA
#> 2 age, Cure model 0.0143 NA NA NA
#> 3 grade_ii, Cure model -0.0135 NA NA NA
#> 4 grade_iii, Cure model 0.819 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000261 NA NA NA
#> 2 grade_ii, Survival model 0.768 NA NA NA
#> 3 grade_iii, Survival model 0.260 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.70115 0.01433 -0.01349 0.81879
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 257.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.70115379 0.01433034 -0.01348739 0.81878711
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0002606304 0.7678177543 0.2595868583
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.21943693 0.82754451 0.60576552 0.86484238 0.96582818 0.31350980
#> [7] 0.55386632 0.82754451 0.60576552 0.25515962 0.14225496 0.38085142
#> [13] 0.25515962 0.98648612 0.36164398 0.68878982 0.02982927 0.57118850
#> [19] 0.79708037 0.55386632 0.77408476 0.02982927 0.60576552 0.31350980
#> [25] 0.93074295 0.47323448 0.09677061 0.71217027 0.94503074 0.64759907
#> [31] 0.25515962 0.15592310 0.50031676 0.81987520 0.94503074 0.58851874
#> [37] 0.73565665 0.50031676 0.19369100 0.90904624 0.66406566 0.67231850
#> [43] 0.78180658 0.47323448 0.68056976 0.68878982 0.97275132 0.51853044
#> [49] 0.84248451 0.39057627 0.44613556 0.15592310 0.84248451 0.40029731
#> [55] 0.51853044 0.90168503 0.79708037 0.34242393 0.87962088 0.18080205
#> [61] 0.63088130 0.68878982 0.75107976 0.44613556 0.30354901 0.47323448
#> [67] 0.88702163 0.93074295 0.31350980 0.72790266 0.34242393 0.23207527
#> [73] 0.94503074 0.36164398 0.02982927 0.40029731 0.12683381 0.85741928
#> [79] 0.91638911 0.20656835 0.57987400 0.24394222 0.43672984 0.25515962
#> [85] 0.40029731 0.86484238 0.53653880 0.25515962 0.75107976 0.75107976
#> [91] 0.09677061 0.79708037 0.88702163 0.02982927 0.59716145 0.53653880
#> [97] 0.97275132 0.91638911 0.98648612 0.72004974 0.40029731 0.73565665
#> [103] 0.08028920 0.78180658 0.63088130 0.64759907 0.44613556 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 136 140 130 56 183 68 184 140.1 130.1 99 129 166 99.1
#> 21.83 12.68 16.47 12.21 9.24 20.62 17.77 12.68 16.47 21.19 23.41 19.98 21.19
#> 25 150 125 24 110 81 184.1 96 24.1 130.2 68.1 101 179
#> 6.32 20.33 15.65 23.89 17.56 14.06 17.77 14.54 23.89 16.47 20.62 9.97 18.63
#> 168 6 187 192 99.2 69 88 155 187.1 23 180 88.1 66
#> 23.72 15.64 9.92 16.44 21.19 23.23 18.37 13.08 9.92 16.92 14.82 18.37 22.13
#> 61 188 100 57 179.1 26 125.1 77 51 177 105 76 69.1
#> 10.12 16.16 16.07 14.46 18.63 15.77 15.65 7.27 18.23 12.53 19.75 19.22 23.23
#> 177.1 170 51.1 10 81.1 128 43 169 181 125.2 133 76.1 190
#> 12.53 19.54 18.23 10.53 14.06 20.35 12.10 22.41 16.46 15.65 14.65 19.22 20.81
#> 179.2 159 101.1 68.2 18 128.1 197 187.2 150.1 24.2 170.1 164 37
#> 18.63 10.55 9.97 20.62 15.21 20.35 21.60 9.92 20.33 23.89 19.54 23.60 12.52
#> 145 175 45 139 58 36 170.2 56.1 40 99.3 133.1 133.2 168.1
#> 10.07 21.91 17.42 21.49 19.34 21.19 19.54 12.21 18.00 21.19 14.65 14.65 23.72
#> 81.2 159.1 24.3 171 40.1 77.1 145.1 25.1 39 170.3 180.1 86 57.1
#> 14.06 10.55 23.89 16.57 18.00 7.27 10.07 6.32 15.59 19.54 14.82 23.81 14.46
#> 181.1 85 76.2 62 27 84 176 80 71 27.1 182 147 35
#> 16.46 16.44 19.22 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 186 34 112 119 161 143 31 98 144 87 151 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 102 75 27.2 182.1 182.2 165 116 12 87.1 109 28 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 67 132 67.1 163 87.2 53 84.1 19 9 173 83 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 33 72 185 142.1 143.1 163.1 84.2 87.3 82 12.1 142.2 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 74 20 38 33.1 33.2 109.1 120 109.2 191.1 191.2 83.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 178.1 174.1 172 186.1 64 31.1 94 35.1 102.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007104708 0.330132982 0.255806742
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.51681776 0.01162253 -0.25138590
#> grade_iii, Cure model
#> 0.85960710
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 140 12.68 1 59 1 0
#> 61 10.12 1 36 0 1
#> 81 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 42 12.43 1 49 0 1
#> 60 13.15 1 38 1 0
#> 97 19.14 1 65 0 1
#> 155 13.08 1 26 0 0
#> 43 12.10 1 61 0 1
#> 177 12.53 1 75 0 0
#> 123 13.00 1 44 1 0
#> 180 14.82 1 37 0 0
#> 100 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 100.1 16.07 1 60 0 0
#> 93 10.33 1 52 0 1
#> 55 19.34 1 69 0 1
#> 125 15.65 1 67 1 0
#> 179 18.63 1 42 0 0
#> 100.2 16.07 1 60 0 0
#> 128 20.35 1 35 0 1
#> 59 10.16 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 63.1 22.77 1 31 1 0
#> 127 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 100.3 16.07 1 60 0 0
#> 129 23.41 1 53 1 0
#> 100.4 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 166 19.98 1 48 0 0
#> 10 10.53 1 34 0 0
#> 168 23.72 1 70 0 0
#> 180.1 14.82 1 37 0 0
#> 113.1 22.86 1 34 0 0
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 70 7.38 1 30 1 0
#> 23 16.92 1 61 0 0
#> 139 21.49 1 63 1 0
#> 139.1 21.49 1 63 1 0
#> 168.1 23.72 1 70 0 0
#> 155.1 13.08 1 26 0 0
#> 145 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 10.1 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 29 15.45 1 68 1 0
#> 197 21.60 1 69 1 0
#> 133 14.65 1 57 0 0
#> 195 11.76 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 133.1 14.65 1 57 0 0
#> 153 21.33 1 55 1 0
#> 76.1 19.22 1 54 0 1
#> 108.1 18.29 1 39 0 1
#> 128.2 20.35 1 35 0 1
#> 166.1 19.98 1 48 0 0
#> 51 18.23 1 83 0 1
#> 39 15.59 1 37 0 1
#> 32 20.90 1 37 1 0
#> 111 17.45 1 47 0 1
#> 88 18.37 1 47 0 0
#> 181.1 16.46 1 45 0 1
#> 52 10.42 1 52 0 1
#> 97.1 19.14 1 65 0 1
#> 155.2 13.08 1 26 0 0
#> 86 23.81 1 58 0 1
#> 199 19.81 1 NA 0 1
#> 25 6.32 1 34 1 0
#> 180.2 14.82 1 37 0 0
#> 39.1 15.59 1 37 0 1
#> 197.1 21.60 1 69 1 0
#> 107 11.18 1 54 1 0
#> 130 16.47 1 53 0 1
#> 168.2 23.72 1 70 0 0
#> 32.1 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 51.1 18.23 1 83 0 1
#> 60.2 13.15 1 38 1 0
#> 197.2 21.60 1 69 1 0
#> 99.1 21.19 1 38 0 1
#> 194 22.40 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 59.1 10.16 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 183 9.24 1 67 1 0
#> 91.1 5.33 1 61 0 1
#> 187 9.92 1 39 1 0
#> 181.2 16.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 157 15.10 1 47 0 0
#> 42.2 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 168.3 23.72 1 70 0 0
#> 76.2 19.22 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 54 24.00 0 53 1 0
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 142.1 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 178.1 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 198 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 82 24.00 0 34 0 0
#> 147 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 54.1 24.00 0 53 1 0
#> 7.1 24.00 0 37 1 0
#> 3 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 121 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 162.1 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 198.1 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 104 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 172.1 24.00 0 41 0 0
#> 163.1 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 1.1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 103.1 24.00 0 56 1 0
#> 20 24.00 0 46 1 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 22 24.00 0 52 1 0
#> 198.2 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 21.1 24.00 0 47 0 0
#> 176.1 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 121.1 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 172.2 24.00 0 41 0 0
#> 176.2 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 54.2 24.00 0 53 1 0
#> 144.1 24.00 0 28 0 1
#> 186.1 24.00 0 45 1 0
#> 22.1 24.00 0 52 1 0
#> 54.3 24.00 0 53 1 0
#> 121.2 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 1.2 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#> 82.1 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 84.1 24.00 0 39 0 1
#> 1.3 24.00 0 23 1 0
#> 54.4 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.517 NA NA NA
#> 2 age, Cure model 0.0116 NA NA NA
#> 3 grade_ii, Cure model -0.251 NA NA NA
#> 4 grade_iii, Cure model 0.860 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00710 NA NA NA
#> 2 grade_ii, Survival model 0.330 NA NA NA
#> 3 grade_iii, Survival model 0.256 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51682 0.01162 -0.25139 0.85961
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 256.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51681776 0.01162253 -0.25138590 0.85960710
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007104708 0.330132982 0.255806742
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.745917705 0.903803770 0.653324029 0.397353165 0.798217112 0.663724366
#> [7] 0.304937642 0.694351417 0.840089423 0.766768115 0.725208216 0.592188201
#> [13] 0.483638965 0.473923964 0.150054420 0.483638965 0.893123263 0.269571910
#> [19] 0.531920483 0.322987857 0.483638965 0.209343927 0.068109079 0.068109079
#> [25] 0.989263450 0.052169721 0.483638965 0.036094159 0.483638965 0.464222602
#> [31] 0.234543066 0.861279120 0.013447628 0.592188201 0.052169721 0.278553682
#> [37] 0.406887779 0.946575164 0.416449291 0.124497040 0.124497040 0.013447628
#> [43] 0.694351417 0.914484275 0.150054420 0.044074972 0.341505734 0.861279120
#> [49] 0.083644613 0.561898323 0.100463932 0.622416681 0.209343927 0.756357772
#> [55] 0.967945680 0.435752872 0.622416681 0.141336216 0.278553682 0.341505734
#> [61] 0.209343927 0.234543066 0.359864847 0.541973508 0.183618386 0.387914911
#> [67] 0.332210160 0.435752872 0.882456459 0.304937642 0.694351417 0.007250231
#> [73] 0.957265944 0.592188201 0.541973508 0.100463932 0.850680833 0.426088644
#> [79] 0.013447628 0.183618386 0.001956381 0.252027750 0.252027750 0.663724366
#> [85] 0.359864847 0.663724366 0.100463932 0.150054420 0.092048602 0.766768115
#> [91] 0.571976229 0.787680451 0.642959103 0.798217112 0.174877242 0.935869379
#> [97] 0.967945680 0.925180192 0.435752872 0.378493891 0.582057307 0.798217112
#> [103] 0.829519697 0.200576109 0.013447628 0.278553682 0.725208216 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 140 61 81 30 42 60 97 155 43 177 123 180 100
#> 12.68 10.12 14.06 17.43 12.43 13.15 19.14 13.08 12.10 12.53 13.00 14.82 16.07
#> 188 36 100.1 93 55 125 179 100.2 128 63 63.1 127 113
#> 16.16 21.19 16.07 10.33 19.34 15.65 18.63 16.07 20.35 22.77 22.77 3.53 22.86
#> 100.3 129 100.4 79 166 10 168 180.1 113.1 76 45 70 23
#> 16.07 23.41 16.07 16.23 19.98 10.53 23.72 14.82 22.86 19.22 17.42 7.38 16.92
#> 139 139.1 168.1 155.1 145 99 92 108 10.1 15 29 197 133
#> 21.49 21.49 23.72 13.08 10.07 21.19 22.92 18.29 10.53 22.68 15.45 21.60 14.65
#> 128.1 154 91 181 133.1 153 76.1 108.1 128.2 166.1 51 39 32
#> 20.35 12.63 5.33 16.46 14.65 21.33 19.22 18.29 20.35 19.98 18.23 15.59 20.90
#> 111 88 181.1 52 97.1 155.2 86 25 180.2 39.1 197.1 107 130
#> 17.45 18.37 16.46 10.42 19.14 13.08 23.81 6.32 14.82 15.59 21.60 11.18 16.47
#> 168.2 32.1 24 170 170.1 60.1 51.1 60.2 197.2 99.1 194 177.1 18
#> 23.72 20.90 23.89 19.54 19.54 13.15 18.23 13.15 21.60 21.19 22.40 12.53 15.21
#> 37 57 42.1 90 183 91.1 187 181.2 41 157 42.2 49 68
#> 12.52 14.46 12.43 20.94 9.24 5.33 9.92 16.46 18.02 15.10 12.43 12.19 20.62
#> 168.3 76.2 123.1 54 193 186 142 17 27 142.1 80 178 138
#> 23.72 19.22 13.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 178.1 7 198 94 82 147 172 54.1 7.1 3 146 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 31 65 162 138.1 163 162.1 200 198.1 176 1 104 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 161 19 172.1 163.1 1.1 11 103 21 126 112 9 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 20 109 141 12 22 198.2 84 21.1 176.1 144 28 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 2 121.1 74 172.2 176.2 64 54.2 144.1 186.1 22.1 54.3 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 3.1 3.2 12.1 1.2 132 82.1 132.1 148 84.1 1.3 54.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01487397 0.67282372 0.55844343
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.164409734 -0.001266247 0.224827849
#> grade_iii, Cure model
#> 1.036184613
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 184 17.77 1 38 0 0
#> 26 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 175 21.91 1 43 0 0
#> 184.1 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 136 21.83 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 41 18.02 1 40 1 0
#> 16 8.71 1 71 0 1
#> 167 15.55 1 56 1 0
#> 167.1 15.55 1 56 1 0
#> 114 13.68 1 NA 0 0
#> 16.1 8.71 1 71 0 1
#> 52 10.42 1 52 0 1
#> 179.1 18.63 1 42 0 0
#> 25.1 6.32 1 34 1 0
#> 100 16.07 1 60 0 0
#> 78 23.88 1 43 0 0
#> 43 12.10 1 61 0 1
#> 197 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 66 22.13 1 53 0 0
#> 190 20.81 1 42 1 0
#> 13.1 14.34 1 54 0 1
#> 194 22.40 1 38 0 1
#> 136.1 21.83 1 43 0 1
#> 24 23.89 1 38 0 0
#> 61 10.12 1 36 0 1
#> 77 7.27 1 67 0 1
#> 37.1 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 69 23.23 1 25 0 1
#> 149 8.37 1 33 1 0
#> 58 19.34 1 39 0 0
#> 56 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 167.2 15.55 1 56 1 0
#> 10 10.53 1 34 0 0
#> 127 3.53 1 62 0 1
#> 194.1 22.40 1 38 0 1
#> 24.1 23.89 1 38 0 0
#> 154 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 5 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 184.2 17.77 1 38 0 0
#> 111.1 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 197.1 21.60 1 69 1 0
#> 153 21.33 1 55 1 0
#> 66.1 22.13 1 53 0 0
#> 171 16.57 1 41 0 1
#> 66.2 22.13 1 53 0 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 93 10.33 1 52 0 1
#> 179.2 18.63 1 42 0 0
#> 183 9.24 1 67 1 0
#> 86 23.81 1 58 0 1
#> 39 15.59 1 37 0 1
#> 124 9.73 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 13.2 14.34 1 54 0 1
#> 89.1 11.44 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 91 5.33 1 61 0 1
#> 139 21.49 1 63 1 0
#> 169 22.41 1 46 0 0
#> 41.1 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 25.2 6.32 1 34 1 0
#> 170.1 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 89.2 11.44 1 NA 0 0
#> 167.3 15.55 1 56 1 0
#> 125 15.65 1 67 1 0
#> 108 18.29 1 39 0 1
#> 4.1 17.64 1 NA 0 1
#> 89.3 11.44 1 NA 0 0
#> 61.1 10.12 1 36 0 1
#> 60 13.15 1 38 1 0
#> 149.1 8.37 1 33 1 0
#> 6 15.64 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 134.1 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 181.1 16.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 32.1 20.90 1 37 1 0
#> 93.1 10.33 1 52 0 1
#> 70.1 7.38 1 30 1 0
#> 100.1 16.07 1 60 0 0
#> 184.3 17.77 1 38 0 0
#> 69.1 23.23 1 25 0 1
#> 144 24.00 0 28 0 1
#> 109 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 118.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 80 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 109.1 24.00 0 48 0 0
#> 80.1 24.00 0 41 0 0
#> 148.1 24.00 0 61 1 0
#> 72 24.00 0 40 0 1
#> 193 24.00 0 45 0 1
#> 109.2 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 80.2 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 84 24.00 0 39 0 1
#> 9 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 75 24.00 0 21 1 0
#> 12.1 24.00 0 63 0 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 31.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 9.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 3 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 62.1 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 11.1 24.00 0 42 0 1
#> 75.1 24.00 0 21 1 0
#> 165 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 54.1 24.00 0 53 1 0
#> 143.1 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 115 24.00 0 NA 1 0
#> 147.1 24.00 0 76 1 0
#> 161.1 24.00 0 45 0 0
#> 178 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 176 24.00 0 43 0 1
#> 7 24.00 0 37 1 0
#> 72.1 24.00 0 40 0 1
#> 62.2 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 148.2 24.00 0 61 1 0
#> 1 24.00 0 23 1 0
#> 22.1 24.00 0 52 1 0
#> 148.3 24.00 0 61 1 0
#> 98.1 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 182.1 24.00 0 35 0 0
#> 27 24.00 0 63 1 0
#> 12.2 24.00 0 63 0 0
#> 2.1 24.00 0 9 0 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.164 NA NA NA
#> 2 age, Cure model -0.00127 NA NA NA
#> 3 grade_ii, Cure model 0.225 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0149 NA NA NA
#> 2 grade_ii, Survival model 0.673 NA NA NA
#> 3 grade_iii, Survival model 0.558 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.164410 -0.001266 0.224828 1.036185
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 247.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.164409734 -0.001266247 0.224827849 1.036184613
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01487397 0.67282372 0.55844343
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7616370 0.8424457 0.6977259 0.9846823 0.5406011 0.7616370 0.7045523
#> [8] 0.5665784 0.9113672 0.8831102 0.7374540 0.9587375 0.8615365 0.8615365
#> [15] 0.9587375 0.9302909 0.7045523 0.9846823 0.8325538 0.2601086 0.9228010
#> [22] 0.5900650 0.8171096 0.6906506 0.7845288 0.5003989 0.6531359 0.8831102
#> [29] 0.4702844 0.5665784 0.1473571 0.9412127 0.9783821 0.9113672 0.8788439
#> [36] 0.3733448 0.9653817 0.6833585 0.9189997 0.4149290 0.8066090 0.9518367
#> [43] 0.8615365 0.9265510 0.9969749 0.4702844 0.1473571 0.9074247 0.7498322
#> [50] 0.8223529 0.9719267 0.7243395 0.7616370 0.7845288 0.5406011 0.5900650
#> [57] 0.6194357 0.5003989 0.8011701 0.5003989 0.6283970 0.7956481 0.9339895
#> [64] 0.7045523 0.9553140 0.3128614 0.8568434 0.6370288 0.8831102 0.6687299
#> [71] 0.9939183 0.6100049 0.4525871 0.7374540 0.4341831 0.9783821 0.9846823
#> [78] 0.6687299 0.8953356 0.8615365 0.8473309 0.7309592 0.9412127 0.8994172
#> [85] 0.9653817 0.8520976 0.7498322 0.8275064 0.9034539 0.8066090 0.9483274
#> [92] 0.6609808 0.3473713 0.6370288 0.9339895 0.9719267 0.8325538 0.7616370
#> [99] 0.3733448 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 184 26 97 25 175 184.1 179 136 37 13 41 16 167
#> 17.77 15.77 19.14 6.32 21.91 17.77 18.63 21.83 12.52 14.34 18.02 8.71 15.55
#> 167.1 16.1 52 179.1 25.1 100 78 43 197 85 76 111 66
#> 15.55 8.71 10.42 18.63 6.32 16.07 23.88 12.10 21.60 16.44 19.22 17.45 22.13
#> 190 13.1 194 136.1 24 61 77 37.1 29 69 149 58 56
#> 20.81 14.34 22.40 21.83 23.89 10.12 7.27 12.52 15.45 23.23 8.37 19.34 12.21
#> 63 181 187 167.2 10 127 194.1 24.1 154 134 5 70 8
#> 22.77 16.46 9.92 15.55 10.53 3.53 22.40 23.89 12.63 17.81 16.43 7.38 18.43
#> 184.2 111.1 175.1 197.1 153 66.1 171 66.2 90 23 93 179.2 183
#> 17.77 17.45 21.91 21.60 21.33 22.13 16.57 22.13 20.94 16.92 10.33 18.63 9.24
#> 86 39 32 13.2 170 91 139 169 41.1 15 77.1 25.2 170.1
#> 23.81 15.59 20.90 14.34 19.54 5.33 21.49 22.41 18.02 22.68 7.27 6.32 19.54
#> 81 167.3 125 108 61.1 60 149.1 6 134.1 79 140 181.1 145
#> 14.06 15.55 15.65 18.29 10.12 13.15 8.37 15.64 17.81 16.23 12.68 16.46 10.07
#> 166 129 32.1 93.1 70.1 100.1 184.3 69.1 144 109 31 143 54
#> 19.98 23.41 20.90 10.33 7.38 16.07 17.77 23.23 24.00 24.00 24.00 24.00 24.00
#> 122 19 65 82 118 198 98 12 118.1 132 191 146 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 80 151 102 109.1 80.1 148.1 72 193 109.2 198.1 80.2 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 84 9 2 147 75 12.1 87 121 46 156 31.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 9.1 163 62 112 161 3 141 138 11 62.1 196 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 165 146.1 182 54.1 143.1 112.1 147.1 161.1 178 74 176 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 62.2 22 148.2 1 22.1 148.3 98.1 160 21 82.1 182.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.2 2.1 160.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02099979 0.28872831 0.34485884
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 1.07491553 -0.02669057 0.31381097
#> grade_iii, Cure model
#> 0.65018218
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 130 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 153 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 97 19.14 1 65 0 1
#> 180 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 60 13.15 1 38 1 0
#> 111 17.45 1 47 0 1
#> 45 17.42 1 54 0 1
#> 96 14.54 1 33 0 1
#> 90 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 168 23.72 1 70 0 0
#> 89 11.44 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 124 9.73 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 60.1 13.15 1 38 1 0
#> 111.1 17.45 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 153.1 21.33 1 55 1 0
#> 8 18.43 1 32 0 0
#> 181 16.46 1 45 0 1
#> 166.1 19.98 1 48 0 0
#> 107 11.18 1 54 1 0
#> 117 17.46 1 26 0 1
#> 145 10.07 1 65 1 0
#> 89.2 11.44 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 194 22.40 1 38 0 1
#> 32 20.90 1 37 1 0
#> 68 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 175 21.91 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 139 21.49 1 63 1 0
#> 170 19.54 1 43 0 1
#> 188 16.16 1 46 0 1
#> 14 12.89 1 21 0 0
#> 130.1 16.47 1 53 0 1
#> 159 10.55 1 50 0 1
#> 197 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 63 22.77 1 31 1 0
#> 96.1 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 158 20.14 1 74 1 0
#> 195 11.76 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 32.1 20.90 1 37 1 0
#> 130.2 16.47 1 53 0 1
#> 154 12.63 1 20 1 0
#> 59 10.16 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 41.2 18.02 1 40 1 0
#> 24.1 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 81.1 14.06 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 130.3 16.47 1 53 0 1
#> 97.1 19.14 1 65 0 1
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 32.2 20.90 1 37 1 0
#> 25 6.32 1 34 1 0
#> 129 23.41 1 53 1 0
#> 139.1 21.49 1 63 1 0
#> 5 16.43 1 51 0 1
#> 25.1 6.32 1 34 1 0
#> 197.1 21.60 1 69 1 0
#> 40 18.00 1 28 1 0
#> 108.1 18.29 1 39 0 1
#> 199.1 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 125 15.65 1 67 1 0
#> 114.1 13.68 1 NA 0 0
#> 107.1 11.18 1 54 1 0
#> 90.2 20.94 1 50 0 1
#> 155.1 13.08 1 26 0 0
#> 15.1 22.68 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 150 20.33 1 48 0 0
#> 77 7.27 1 67 0 1
#> 167 15.55 1 56 1 0
#> 23 16.92 1 61 0 0
#> 25.2 6.32 1 34 1 0
#> 129.1 23.41 1 53 1 0
#> 14.1 12.89 1 21 0 0
#> 4 17.64 1 NA 0 1
#> 60.2 13.15 1 38 1 0
#> 58 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 154.2 12.63 1 20 1 0
#> 129.2 23.41 1 53 1 0
#> 155.2 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 41.3 18.02 1 40 1 0
#> 129.3 23.41 1 53 1 0
#> 6.1 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 195.1 11.76 1 NA 1 0
#> 165 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 146 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 65 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 165.1 24.00 0 47 0 0
#> 135.1 24.00 0 58 1 0
#> 198 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 38 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 146.2 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 120.1 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 146.3 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 135.2 24.00 0 58 1 0
#> 122 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 22 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 3.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 165.2 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 172.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 126.1 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 126.2 24.00 0 48 0 0
#> 120.2 24.00 0 68 0 1
#> 11.1 24.00 0 42 0 1
#> 178.2 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 87.1 24.00 0 27 0 0
#> 161 24.00 0 45 0 0
#> 198.1 24.00 0 66 0 1
#> 148.1 24.00 0 61 1 0
#> 74.1 24.00 0 43 0 1
#> 132.1 24.00 0 55 0 0
#> 53 24.00 0 32 0 1
#> 33.2 24.00 0 53 0 0
#> 38.1 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 1.07 NA NA NA
#> 2 age, Cure model -0.0267 NA NA NA
#> 3 grade_ii, Cure model 0.314 NA NA NA
#> 4 grade_iii, Cure model 0.650 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0210 NA NA NA
#> 2 grade_ii, Survival model 0.289 NA NA NA
#> 3 grade_iii, Survival model 0.345 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 1.07492 -0.02669 0.31381 0.65018
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 248.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 1.07491553 -0.02669057 0.31381097 0.65018218
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02099979 0.28872831 0.34485884
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.755926e-01 5.723247e-03 3.724564e-02 3.317887e-01 1.782618e-01
#> [6] 4.538965e-05 1.279698e-01 4.614087e-01 1.607411e-01 2.040936e-02
#> [11] 1.284059e-02 5.648657e-01 2.341418e-01 2.542731e-01 4.901009e-01
#> [16] 5.036874e-02 3.936341e-01 5.343387e-01 8.933912e-04 7.594513e-01
#> [21] 5.648657e-01 2.341418e-01 9.943376e-02 1.782618e-01 3.724564e-02
#> [26] 1.437466e-01 3.198912e-01 9.943376e-02 7.943730e-01 2.242620e-01
#> [31] 8.665433e-01 4.200649e-01 1.519318e-02 6.487433e-02 8.076232e-02
#> [36] 1.520950e-01 1.768701e-02 5.036874e-02 4.573918e-02 4.183677e-04
#> [41] 2.974592e-02 1.131578e-01 3.683357e-01 6.597267e-01 2.755926e-01
#> [46] 8.299966e-01 2.329680e-02 3.317887e-01 7.288023e-03 4.901009e-01
#> [51] 8.482036e-01 9.291124e-02 7.768115e-01 6.487433e-02 2.755926e-01
#> [56] 6.928506e-01 7.423708e-01 1.782618e-01 4.538965e-05 5.343387e-01
#> [61] 6.928506e-01 2.755926e-01 1.279698e-01 6.115220e-01 6.487433e-02
#> [66] 9.422396e-01 1.704462e-03 2.974592e-02 3.558651e-01 9.422396e-01
#> [71] 2.329680e-02 2.144610e-01 1.607411e-01 8.963140e-03 4.614087e-01
#> [76] 4.067050e-01 7.943730e-01 5.036874e-02 6.115220e-01 8.963140e-03
#> [81] 3.683357e-01 8.670168e-02 9.229964e-01 4.473137e-01 2.647779e-01
#> [86] 9.422396e-01 1.704462e-03 6.597267e-01 5.648657e-01 1.204365e-01
#> [91] 9.040122e-01 6.928506e-01 1.704462e-03 6.115220e-01 5.192959e-01
#> [96] 1.782618e-01 1.704462e-03 4.200649e-01 8.851425e-01 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 130 69 153 192 41 24 97 180 108 136 169 60 111
#> 16.47 23.23 21.33 16.44 18.02 23.89 19.14 14.82 18.29 21.83 22.41 13.15 17.45
#> 45 96 90 26 81 168 56 60.1 111.1 166 41.1 153.1 8
#> 17.42 14.54 20.94 15.77 14.06 23.72 12.21 13.15 17.45 19.98 18.02 21.33 18.43
#> 181 166.1 107 117 145 6 194 32 68 88 175 90.1 99
#> 16.46 19.98 11.18 17.46 10.07 15.64 22.40 20.90 20.62 18.37 21.91 20.94 21.19
#> 86 139 170 188 14 130.1 159 197 85 63 96.1 61 158
#> 23.81 21.49 19.54 16.16 12.89 16.47 10.55 21.60 16.44 22.77 14.54 10.12 20.14
#> 49 32.1 130.2 154 42 41.2 24.1 81.1 154.1 130.3 97.1 155 32.2
#> 12.19 20.90 16.47 12.63 12.43 18.02 23.89 14.06 12.63 16.47 19.14 13.08 20.90
#> 25 129 139.1 5 25.1 197.1 40 108.1 15 180.1 125 107.1 90.2
#> 6.32 23.41 21.49 16.43 6.32 21.60 18.00 18.29 22.68 14.82 15.65 11.18 20.94
#> 155.1 15.1 188.1 150 77 167 23 25.2 129.1 14.1 60.2 58 70
#> 13.08 22.68 16.16 20.33 7.27 15.55 16.92 6.32 23.41 12.89 13.15 19.34 7.38
#> 154.2 129.2 155.2 13 41.3 129.3 6.1 16 165 147 146 135 46
#> 12.63 23.41 13.08 14.34 18.02 23.41 15.64 8.71 24.00 24.00 24.00 24.00 24.00
#> 120 84 67 178 87 65 131 118 54 80 156 1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 126 9 121 178.1 27 28 165.1 135.1 198 47 38 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 146.1 182 132 19 74 3 146.2 148 120.1 31 146.3 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.2 122 75 22 17 119 33 28.1 11 3.1 62 33.1 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 200 72 172.1 94 144 138 94.1 126.1 95 102 104 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 120.2 11.1 178.2 193 87.1 161 198.1 148.1 74.1 132.1 53 33.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 80.1 21
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007240729 0.769143733 0.252110917
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.22110584 0.00320813 0.06447885
#> grade_iii, Cure model
#> 0.65352754
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 85 16.44 1 36 0 0
#> 199 19.81 1 NA 0 1
#> 85.1 16.44 1 36 0 0
#> 89 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 61 10.12 1 36 0 1
#> 81 14.06 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 167 15.55 1 56 1 0
#> 49 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 55 19.34 1 69 0 1
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 108 18.29 1 39 0 1
#> 70 7.38 1 30 1 0
#> 29.1 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 106 16.67 1 49 1 0
#> 49.1 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 32 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 149 8.37 1 33 1 0
#> 42.1 12.43 1 49 0 1
#> 105.1 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 150 20.33 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 26 15.77 1 49 0 1
#> 85.2 16.44 1 36 0 0
#> 85.3 16.44 1 36 0 0
#> 45 17.42 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 110 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 36 21.19 1 48 0 1
#> 81.1 14.06 1 34 0 0
#> 24 23.89 1 38 0 0
#> 76.1 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 8.1 18.43 1 32 0 0
#> 154 12.63 1 20 1 0
#> 155 13.08 1 26 0 0
#> 88.1 18.37 1 47 0 0
#> 25 6.32 1 34 1 0
#> 6 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 89.1 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 117 17.46 1 26 0 1
#> 52.2 10.42 1 52 0 1
#> 140 12.68 1 59 1 0
#> 57 14.46 1 45 0 1
#> 88.2 18.37 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 107 11.18 1 54 1 0
#> 68.1 20.62 1 44 0 0
#> 100 16.07 1 60 0 0
#> 81.2 14.06 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 145.1 10.07 1 65 1 0
#> 124.1 9.73 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 50.1 10.02 1 NA 1 0
#> 42.2 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 55.1 19.34 1 69 0 1
#> 66 22.13 1 53 0 0
#> 194 22.40 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 157 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 55.2 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 187.1 9.92 1 39 1 0
#> 50.2 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 158 20.14 1 74 1 0
#> 106.1 16.67 1 49 1 0
#> 166.1 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 66.1 22.13 1 53 0 0
#> 125 15.65 1 67 1 0
#> 13 14.34 1 54 0 1
#> 6.1 15.64 1 39 0 0
#> 107.1 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 42.3 12.43 1 49 0 1
#> 68.2 20.62 1 44 0 0
#> 14 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 130 16.47 1 53 0 1
#> 128.1 20.35 1 35 0 1
#> 5 16.43 1 51 0 1
#> 91.1 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 192 16.44 1 31 1 0
#> 145.2 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 42.4 12.43 1 49 0 1
#> 181.1 16.46 1 45 0 1
#> 115 24.00 0 NA 1 0
#> 120 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 119.1 24.00 0 17 0 0
#> 48 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 119.2 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 119.3 24.00 0 17 0 0
#> 109 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 185.1 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 112 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 48.1 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 102 24.00 0 49 0 0
#> 198.1 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 94.1 24.00 0 51 0 1
#> 165 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 120.2 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 118.1 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 12 24.00 0 63 0 0
#> 193.2 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 161.2 24.00 0 45 0 0
#> 74 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 126 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 122 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 17 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 143.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 80 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 182.2 24.00 0 35 0 0
#> 67.1 24.00 0 25 0 0
#> 54.1 24.00 0 53 1 0
#> 72 24.00 0 40 0 1
#> 103.2 24.00 0 56 1 0
#> 116.1 24.00 0 58 0 1
#> 102.1 24.00 0 49 0 0
#> 27 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 104.1 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 20.1 24.00 0 46 1 0
#> 109.1 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.221 NA NA NA
#> 2 age, Cure model 0.00321 NA NA NA
#> 3 grade_ii, Cure model 0.0645 NA NA NA
#> 4 grade_iii, Cure model 0.654 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00724 NA NA NA
#> 2 grade_ii, Survival model 0.769 NA NA NA
#> 3 grade_iii, Survival model 0.252 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.221106 0.003208 0.064479 0.653528
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 256.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.22110584 0.00320813 0.06447885 0.65352754
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007240729 0.769143733 0.252110917
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.277098730 0.440896258 0.440896258 0.563861395 0.872018038 0.636436470
#> [7] 0.257718452 0.553410049 0.770721276 0.821362203 0.201677323 0.247993487
#> [13] 0.605131164 0.306531668 0.951785239 0.563861395 0.174269979 0.389602195
#> [19] 0.770721276 0.720117267 0.098165626 0.831531287 0.089906342 0.316684616
#> [25] 0.941934346 0.720117267 0.174269979 0.229115227 0.139276239 0.316684616
#> [31] 0.511582680 0.440896258 0.440896258 0.378977605 0.831531287 0.022272741
#> [37] 0.011944693 0.347458525 0.912200714 0.066046657 0.636436470 0.003201316
#> [43] 0.229115227 0.122474182 0.257718452 0.699363159 0.667617228 0.277098730
#> [49] 0.961561601 0.532533480 0.156805160 0.066046657 0.357935099 0.831531287
#> [55] 0.688817544 0.615550365 0.277098730 0.882241709 0.791089979 0.098165626
#> [61] 0.501093803 0.636436470 0.961561601 0.882241709 0.420359261 0.720117267
#> [67] 0.811220519 0.201677323 0.039461469 0.030832031 0.066046657 0.584330761
#> [73] 0.980748276 0.192375188 0.201677323 0.594709588 0.912200714 0.057092536
#> [79] 0.148108749 0.389602195 0.156805160 0.368391516 0.039461469 0.522092592
#> [85] 0.625982120 0.532533480 0.791089979 0.932010885 0.720117267 0.098165626
#> [91] 0.678205699 0.337043616 0.409998707 0.122474182 0.490681730 0.980748276
#> [97] 0.861795389 0.440896258 0.882241709 0.709772694 0.720117267 0.420359261
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 88 85 85.1 29 61 81 8 167 49 10 55 179 96
#> 18.37 16.44 16.44 15.45 10.12 14.06 18.43 15.55 12.19 10.53 19.34 18.63 14.54
#> 108 70 29.1 105 106 49.1 42 68 52 32 51 149 42.1
#> 18.29 7.38 15.45 19.75 16.67 12.19 12.43 20.62 10.42 20.90 18.23 8.37 12.43
#> 105.1 76 150 51.1 26 85.2 85.3 45 52.1 129 86 110 187
#> 19.75 19.22 20.33 18.23 15.77 16.44 16.44 17.42 10.42 23.41 23.81 17.56 9.92
#> 36 81.1 24 76.1 128 8.1 154 155 88.1 25 6 166 99
#> 21.19 14.06 23.89 19.22 20.35 18.43 12.63 13.08 18.37 6.32 15.64 19.98 21.19
#> 117 52.2 140 57 88.2 145 107 68.1 100 81.2 25.1 145.1 181
#> 17.46 10.42 12.68 14.46 18.37 10.07 11.18 20.62 16.07 14.06 6.32 10.07 16.46
#> 42.2 159 55.1 66 194 99.1 157 91 170 55.2 180 187.1 153
#> 12.43 10.55 19.34 22.13 22.40 21.19 15.10 5.33 19.54 19.34 14.82 9.92 21.33
#> 158 106.1 166.1 30 66.1 125 13 6.1 107.1 183 42.3 68.2 14
#> 20.14 16.67 19.98 17.43 22.13 15.65 14.34 15.64 11.18 9.24 12.43 20.62 12.89
#> 184 130 128.1 5 91.1 93 192 145.2 37 42.4 181.1 120 119
#> 17.77 16.47 20.35 16.43 5.33 10.33 16.44 10.07 12.52 12.43 16.46 24.00 24.00
#> 193 103 119.1 48 54 119.2 120.1 143 119.3 109 118 3 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 185 193.1 185.1 64 94 182 62 198 65 95 67 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 48.1 103.1 102 198.1 176 94.1 165 186 46 156 120.2 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 118.1 161 161.1 12 193.2 38 162 19 132 161.2 74 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 142 152 182.1 122 2.1 17 104 95.1 143.1 44 116 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 11 182.2 67.1 54.1 72 103.2 116.1 102.1 27 27.1 121.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 176.1 20 1 20.1 109.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004786146 0.533294651 0.116637707
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -5.468326e-02 9.461543e-05 -2.967394e-02
#> grade_iii, Cure model
#> 6.916729e-01
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 93 10.33 1 52 0 1
#> 76 19.22 1 54 0 1
#> 125 15.65 1 67 1 0
#> 70 7.38 1 30 1 0
#> 171 16.57 1 41 0 1
#> 113 22.86 1 34 0 0
#> 36 21.19 1 48 0 1
#> 86 23.81 1 58 0 1
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 25 6.32 1 34 1 0
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 6 15.64 1 39 0 0
#> 110.1 17.56 1 65 0 1
#> 113.1 22.86 1 34 0 0
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 113.2 22.86 1 34 0 0
#> 32 20.90 1 37 1 0
#> 129 23.41 1 53 1 0
#> 127.1 3.53 1 62 0 1
#> 195 11.76 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 40.1 18.00 1 28 1 0
#> 140 12.68 1 59 1 0
#> 92 22.92 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 78 23.88 1 43 0 0
#> 56 12.21 1 60 0 0
#> 16 8.71 1 71 0 1
#> 89 11.44 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 81.1 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 86.1 23.81 1 58 0 1
#> 169.1 22.41 1 46 0 0
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 86.2 23.81 1 58 0 1
#> 154 12.63 1 20 1 0
#> 101 9.97 1 10 0 1
#> 30.1 17.43 1 78 0 0
#> 134 17.81 1 47 1 0
#> 164.1 23.60 1 76 0 1
#> 45.1 17.42 1 54 0 1
#> 10.1 10.53 1 34 0 0
#> 50.1 10.02 1 NA 1 0
#> 125.2 15.65 1 67 1 0
#> 56.1 12.21 1 60 0 0
#> 124 9.73 1 NA 1 0
#> 56.2 12.21 1 60 0 0
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 100 16.07 1 60 0 0
#> 23.1 16.92 1 61 0 0
#> 168 23.72 1 70 0 0
#> 77 7.27 1 67 0 1
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 91 5.33 1 61 0 1
#> 110.2 17.56 1 65 0 1
#> 14 12.89 1 21 0 0
#> 181 16.46 1 45 0 1
#> 85.1 16.44 1 36 0 0
#> 86.3 23.81 1 58 0 1
#> 189.1 10.51 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 23.2 16.92 1 61 0 0
#> 18.1 15.21 1 49 1 0
#> 81.2 14.06 1 34 0 0
#> 175.1 21.91 1 43 0 0
#> 134.1 17.81 1 47 1 0
#> 181.1 16.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 149 8.37 1 33 1 0
#> 107 11.18 1 54 1 0
#> 4.1 17.64 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 59 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 170 19.54 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 45.2 17.42 1 54 0 1
#> 25.1 6.32 1 34 1 0
#> 56.3 12.21 1 60 0 0
#> 24 23.89 1 38 0 0
#> 180 14.82 1 37 0 0
#> 49 12.19 1 48 1 0
#> 91.1 5.33 1 61 0 1
#> 150.2 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 32.1 20.90 1 37 1 0
#> 164.2 23.60 1 76 0 1
#> 39 15.59 1 37 0 1
#> 175.2 21.91 1 43 0 0
#> 132 24.00 0 55 0 0
#> 143 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 186 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 65 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 176 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 163 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 126 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 74 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 62.1 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 126.1 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 122 24.00 0 66 0 0
#> 126.2 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 131.1 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 131.2 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 64.1 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 7 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 64.2 24.00 0 43 0 0
#> 200 24.00 0 64 0 0
#> 21.1 24.00 0 47 0 0
#> 163.1 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 138.1 24.00 0 44 1 0
#> 143.2 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 122.1 24.00 0 66 0 0
#> 74.2 24.00 0 43 0 1
#> 185.1 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 122.2 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 72.2 24.00 0 40 0 1
#> 126.3 24.00 0 48 0 0
#> 193.1 24.00 0 45 0 1
#> 31 24.00 0 36 0 1
#> 74.3 24.00 0 43 0 1
#> 74.4 24.00 0 43 0 1
#> 33.1 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 141.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0547 NA NA NA
#> 2 age, Cure model 0.0000946 NA NA NA
#> 3 grade_ii, Cure model -0.0297 NA NA NA
#> 4 grade_iii, Cure model 0.692 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00479 NA NA NA
#> 2 grade_ii, Survival model 0.533 NA NA NA
#> 3 grade_iii, Survival model 0.117 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -5.468e-02 9.462e-05 -2.967e-02 6.917e-01
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -5.468326e-02 9.461543e-05 -2.967394e-02 6.916729e-01
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004786146 0.533294651 0.116637707
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.979660644 0.170867491 0.856947471 0.319494273 0.592495763 0.918700093
#> [7] 0.500144126 0.104918345 0.210006509 0.022546473 0.259357502 0.379743883
#> [13] 0.939189327 0.683628968 0.340269294 0.622642620 0.379743883 0.104918345
#> [19] 0.249415452 0.867244999 0.199808053 0.141991736 0.104918345 0.230071184
#> [25] 0.085660574 0.979660644 0.836506400 0.059177828 0.531064573 0.693836083
#> [31] 0.340269294 0.744798971 0.095239122 0.592495763 0.012288597 0.765245826
#> [37] 0.887844701 0.704063092 0.409072548 0.704063092 0.489809634 0.022546473
#> [43] 0.141991736 0.309183927 0.815974248 0.329848825 0.643140890 0.429169500
#> [49] 0.022546473 0.755060390 0.877549153 0.409072548 0.360201690 0.059177828
#> [55] 0.429169500 0.836506400 0.592495763 0.765245826 0.765245826 0.459235885
#> [61] 0.531064573 0.571813767 0.459235885 0.049758752 0.928934283 0.160954172
#> [67] 0.673428019 0.959390661 0.379743883 0.734497077 0.510494989 0.531064573
#> [73] 0.022546473 0.561529368 0.459235885 0.643140890 0.704063092 0.170867491
#> [79] 0.360201690 0.510494989 0.210006509 0.908411284 0.826260497 0.132434026
#> [85] 0.288724592 0.259357502 0.298939313 0.887844701 0.429169500 0.939189327
#> [91] 0.765245826 0.003703244 0.663263834 0.805708811 0.959390661 0.259357502
#> [97] 0.582144549 0.230071184 0.059177828 0.632886885 0.170867491 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 127 175 93 76 125 70 171 113 36 86 150 110 25
#> 3.53 21.91 10.33 19.22 15.65 7.38 16.57 22.86 21.19 23.81 20.33 17.56 6.32
#> 96 40 6 110.1 113.1 68 61 136 169 113.2 32 129 127.1
#> 14.54 18.00 15.64 17.56 22.86 20.62 10.12 21.83 22.41 22.86 20.90 23.41 3.53
#> 10 164 192 13 40.1 140 92 125.1 78 56 16 81 30
#> 10.53 23.60 16.44 14.34 18.00 12.68 22.92 15.65 23.88 12.21 8.71 14.06 17.43
#> 81.1 106 86.1 169.1 55 43 88 18 45 86.2 154 101 30.1
#> 14.06 16.67 23.81 22.41 19.34 12.10 18.37 15.21 17.42 23.81 12.63 9.97 17.43
#> 134 164.1 45.1 10.1 125.2 56.1 56.2 23 85 100 23.1 168 77
#> 17.81 23.60 17.42 10.53 15.65 12.21 12.21 16.92 16.44 16.07 16.92 23.72 7.27
#> 66 133 91 110.2 14 181 85.1 86.3 79 23.2 18.1 81.2 175.1
#> 22.13 14.65 5.33 17.56 12.89 16.46 16.44 23.81 16.23 16.92 15.21 14.06 21.91
#> 134.1 181.1 99 149 107 63 166 150.1 170 16.1 45.2 25.1 56.3
#> 17.81 16.46 21.19 8.37 11.18 22.77 19.98 20.33 19.54 8.71 17.42 6.32 12.21
#> 24 180 49 91.1 150.2 26 32.1 164.2 39 175.2 132 143 119
#> 23.89 14.82 12.19 5.33 20.33 15.77 20.90 23.60 15.59 21.91 24.00 24.00 24.00
#> 186 2 165 147 84 67 65 131 147.1 28 62 53 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 163 64 9 35 161 126 193 109 72 74 143.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 62.1 33 104 126.1 3 161.1 122 126.2 19 20 22 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 75 54 131.1 80 185 48 74.1 131.2 44.1 64.1 21 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 142 64.2 200 21.1 163.1 137 144 138.1 143.2 71 122.1 74.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 120 120.1 141 186.1 9.1 12 122.2 94 148 72.2 126.3 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 74.3 74.4 33.1 116 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007571903 0.467806549 0.769390286
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.57217902 0.00950509 -0.27348840
#> grade_iii, Cure model
#> 1.28246685
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 100 16.07 1 60 0 0
#> 57 14.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 57.1 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 16 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 168.1 23.72 1 70 0 0
#> 76 19.22 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 4 17.64 1 NA 0 1
#> 36.1 21.19 1 48 0 1
#> 50.1 10.02 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 188.1 16.16 1 46 0 1
#> 13 14.34 1 54 0 1
#> 66.1 22.13 1 53 0 0
#> 57.2 14.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 61 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 36.2 21.19 1 48 0 1
#> 150 20.33 1 48 0 0
#> 4.1 17.64 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 177 12.53 1 75 0 0
#> 195.1 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 5 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 4.2 17.64 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 29 15.45 1 68 1 0
#> 169.1 22.41 1 46 0 0
#> 76.1 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 180 14.82 1 37 0 0
#> 100.1 16.07 1 60 0 0
#> 91.1 5.33 1 61 0 1
#> 123 13.00 1 44 1 0
#> 13.1 14.34 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 26 15.77 1 49 0 1
#> 190 20.81 1 42 1 0
#> 59 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 68 20.62 1 44 0 0
#> 139 21.49 1 63 1 0
#> 14 12.89 1 21 0 0
#> 8.1 18.43 1 32 0 0
#> 29.1 15.45 1 68 1 0
#> 4.3 17.64 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 41 18.02 1 40 1 0
#> 52 10.42 1 52 0 1
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 181 16.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 188.2 16.16 1 46 0 1
#> 157 15.10 1 47 0 0
#> 179.1 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 40 18.00 1 28 1 0
#> 56 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 63.2 22.77 1 31 1 0
#> 76.2 19.22 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 32 20.90 1 37 1 0
#> 25 6.32 1 34 1 0
#> 179.2 18.63 1 42 0 0
#> 108 18.29 1 39 0 1
#> 5.1 16.43 1 51 0 1
#> 5.2 16.43 1 51 0 1
#> 13.2 14.34 1 54 0 1
#> 180.1 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 195.2 11.76 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 37.2 12.52 1 57 1 0
#> 13.3 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 111.2 17.45 1 47 0 1
#> 5.3 16.43 1 51 0 1
#> 63.3 22.77 1 31 1 0
#> 57.3 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 128.1 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 18.1 15.21 1 49 1 0
#> 168.2 23.72 1 70 0 0
#> 183.1 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 91.2 5.33 1 61 0 1
#> 52.1 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 129 23.41 1 53 1 0
#> 62 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 148 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 196.1 24.00 0 19 0 0
#> 62.1 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 121.1 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 137 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 151.1 24.00 0 42 0 0
#> 156 24.00 0 50 1 0
#> 119 24.00 0 17 0 0
#> 138.1 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 119.1 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 137.1 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 138.2 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 44.1 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 98 24.00 0 34 1 0
#> 22 24.00 0 52 1 0
#> 20.1 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 73 24.00 0 NA 0 1
#> 115.1 24.00 0 NA 1 0
#> 17.2 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 87 24.00 0 27 0 0
#> 38 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 7.1 24.00 0 37 1 0
#> 116 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 146.1 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 151.2 24.00 0 42 0 0
#> 135 24.00 0 58 1 0
#> 46.1 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 146.2 24.00 0 63 1 0
#> 9.2 24.00 0 31 1 0
#> 20.2 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 135.1 24.00 0 58 1 0
#> 67 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 122.1 24.00 0 66 0 0
#> 196.2 24.00 0 19 0 0
#> 44.2 24.00 0 56 0 0
#> 156.2 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 173.1 24.00 0 19 0 1
#> 104.1 24.00 0 50 1 0
#> 163.1 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.572 NA NA NA
#> 2 age, Cure model 0.00951 NA NA NA
#> 3 grade_ii, Cure model -0.273 NA NA NA
#> 4 grade_iii, Cure model 1.28 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00757 NA NA NA
#> 2 grade_ii, Survival model 0.468 NA NA NA
#> 3 grade_iii, Survival model 0.769 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.572179 0.009505 -0.273488 1.282467
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 236.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.57217902 0.00950509 -0.27348840 1.28246685
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007571903 0.467806549 0.769390286
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.65513675 0.14820560 0.90676615 0.80285578 0.86790573 0.69414537
#> [7] 0.78582495 0.45124765 0.86790573 0.93031483 0.97494106 0.70164563
#> [13] 0.14820560 0.58939663 0.45124765 0.38722244 0.98771809 0.67130052
#> [19] 0.78582495 0.88781375 0.38722244 0.86790573 0.84153678 0.96190588
#> [25] 0.26354292 0.70894833 0.45124765 0.55014724 0.35238369 0.92562945
#> [31] 0.63880135 0.76214756 0.07198808 0.26354292 0.52988014 0.83078487
#> [37] 0.35238369 0.58939663 0.61428485 0.85740085 0.80285578 0.98771809
#> [43] 0.91153447 0.88781375 0.93031483 0.81415795 0.50778136 0.96630077
#> [49] 0.51887726 0.43633806 0.92092586 0.63880135 0.83078487 0.57035929
#> [55] 0.67900941 0.95306221 0.71613057 0.82527176 0.74283905 0.74934317
#> [61] 0.78582495 0.85211120 0.61428485 0.71613057 0.68661799 0.94853749
#> [67] 0.94400032 0.26354292 0.58939663 0.91153447 0.97921961 0.49638817
#> [73] 0.98347863 0.61428485 0.66331216 0.76214756 0.76214756 0.88781375
#> [79] 0.85740085 0.56029321 0.42058206 0.93031483 0.88781375 0.45124765
#> [85] 0.71613057 0.76214756 0.26354292 0.86790573 0.73621695 0.58008400
#> [91] 0.52988014 0.81974596 0.84153678 0.14820560 0.96630077 0.33372414
#> [97] 0.98771809 0.95306221 0.74934317 0.23543473 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 88 168 81 100 57 184 188 36 57.1 37 16 110 168.1
#> 18.37 23.72 14.06 16.07 14.46 17.77 16.16 21.19 14.46 12.52 8.71 17.56 23.72
#> 76 36.1 66 91 51 188.1 13 66.1 57.2 18 61 63 117
#> 19.22 21.19 22.13 5.33 18.23 16.16 14.34 22.13 14.46 15.21 10.12 22.77 17.46
#> 36.2 150 169 177 8 5 78 63.1 128 29 169.1 76.1 179
#> 21.19 20.33 22.41 12.53 18.43 16.43 23.88 22.77 20.35 15.45 22.41 19.22 18.63
#> 180 100.1 91.1 123 13.1 37.1 26 190 183 68 139 14 8.1
#> 14.82 16.07 5.33 13.00 14.34 12.52 15.77 20.81 9.24 20.62 21.49 12.89 18.43
#> 29.1 170 41 52 111 6 181 192 188.2 157 179.1 111.1 40
#> 15.45 19.54 18.02 10.42 17.45 15.64 16.46 16.44 16.16 15.10 18.63 17.45 18.00
#> 56 42 63.2 76.2 123.1 149 32 25 179.2 108 5.1 5.2 13.2
#> 12.21 12.43 22.77 19.22 13.00 8.37 20.90 6.32 18.63 18.29 16.43 16.43 14.34
#> 180.1 166 136 37.2 13.3 99 111.2 5.3 63.3 57.3 130 55 128.1
#> 14.82 19.98 21.83 12.52 14.34 21.19 17.45 16.43 22.77 14.46 16.47 19.34 20.35
#> 125 18.1 168.2 183.1 15 91.2 52.1 85 129 62 9 11 121
#> 15.65 15.21 23.72 9.24 22.68 5.33 10.42 16.44 23.41 24.00 24.00 24.00 24.00
#> 196 186 151 146 19 141 200 148 173 193 33 9.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 122 7 196.1 62.1 54 104 121.1 83 137 162 20 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 156 119 138.1 19.1 119.1 17 137.1 17.1 142 138.2 46 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 103 98 22 20.1 143 162.1 119.2 17.2 28 87 38 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 116 35 156.1 146.1 132 151.2 135 46.1 94 146.2 9.2 20.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 135.1 67 163 84 122.1 196.2 44.2 156.2 84.1 161 65 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 104.1 163.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005216946 0.833838570 0.266354086
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86531293 0.01646146 0.19151731
#> grade_iii, Cure model
#> 0.70687790
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 42 12.43 1 49 0 1
#> 100 16.07 1 60 0 0
#> 49 12.19 1 48 1 0
#> 24 23.89 1 38 0 0
#> 170 19.54 1 43 0 1
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 117 17.46 1 26 0 1
#> 55 19.34 1 69 0 1
#> 15 22.68 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 24.1 23.89 1 38 0 0
#> 56 12.21 1 60 0 0
#> 86.1 23.81 1 58 0 1
#> 85 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 170.1 19.54 1 43 0 1
#> 124 9.73 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 50 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 24.2 23.89 1 38 0 0
#> 89 11.44 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 181 16.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 108 18.29 1 39 0 1
#> 15.1 22.68 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 85.1 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 40.1 18.00 1 28 1 0
#> 187 9.92 1 39 1 0
#> 91 5.33 1 61 0 1
#> 70 7.38 1 30 1 0
#> 14 12.89 1 21 0 0
#> 177 12.53 1 75 0 0
#> 60 13.15 1 38 1 0
#> 76 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 79 16.23 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 92 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 128 20.35 1 35 0 1
#> 184 17.77 1 38 0 0
#> 105.2 19.75 1 60 0 0
#> 157 15.10 1 47 0 0
#> 101 9.97 1 10 0 1
#> 171 16.57 1 41 0 1
#> 43 12.10 1 61 0 1
#> 16.1 8.71 1 71 0 1
#> 164 23.60 1 76 0 1
#> 127 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 51 18.23 1 83 0 1
#> 157.1 15.10 1 47 0 0
#> 108.1 18.29 1 39 0 1
#> 23 16.92 1 61 0 0
#> 166 19.98 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 93 10.33 1 52 0 1
#> 93.1 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 175.1 21.91 1 43 0 0
#> 51.1 18.23 1 83 0 1
#> 13 14.34 1 54 0 1
#> 85.2 16.44 1 36 0 0
#> 158.1 20.14 1 74 1 0
#> 106.1 16.67 1 49 1 0
#> 56.1 12.21 1 60 0 0
#> 107 11.18 1 54 1 0
#> 29 15.45 1 68 1 0
#> 177.1 12.53 1 75 0 0
#> 158.2 20.14 1 74 1 0
#> 150 20.33 1 48 0 0
#> 70.1 7.38 1 30 1 0
#> 86.2 23.81 1 58 0 1
#> 189.1 10.51 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 59.1 10.16 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 175.2 21.91 1 43 0 0
#> 86.3 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 25 6.32 1 34 1 0
#> 175.3 21.91 1 43 0 0
#> 69.1 23.23 1 25 0 1
#> 92.1 22.92 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 50.1 10.02 1 NA 1 0
#> 65 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 20 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 178 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 196 24.00 0 19 0 0
#> 80.2 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 131.1 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 131.2 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 80.3 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 173 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 196.1 24.00 0 19 0 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 126 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 34.1 24.00 0 36 0 0
#> 118.1 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 121 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 176 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 152.1 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 176.1 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 2.1 24.00 0 9 0 0
#> 119 24.00 0 17 0 0
#> 198 24.00 0 66 0 1
#> 21 24.00 0 47 0 0
#> 95.1 24.00 0 68 0 1
#> 71.2 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 67.2 24.00 0 25 0 0
#> 121.1 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 131.3 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 2.2 24.00 0 9 0 0
#> 116.2 24.00 0 58 0 1
#> 160.1 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 126.1 24.00 0 48 0 0
#> 20.1 24.00 0 46 1 0
#> 73.1 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 19.1 24.00 0 57 0 1
#> 161.2 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.865 NA NA NA
#> 2 age, Cure model 0.0165 NA NA NA
#> 3 grade_ii, Cure model 0.192 NA NA NA
#> 4 grade_iii, Cure model 0.707 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00522 NA NA NA
#> 2 grade_ii, Survival model 0.834 NA NA NA
#> 3 grade_iii, Survival model 0.266 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86531 0.01646 0.19152 0.70688
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86531293 0.01646146 0.19151731 0.70687790
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005216946 0.833838570 0.266354086
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.55993929 0.81730410 0.66596370 0.85455251 0.01010366 0.35761118
#> [7] 0.25665964 0.04647650 0.52027521 0.37785520 0.15755794 0.48096941
#> [13] 0.71408873 0.74289094 0.01010366 0.83587254 0.04647650 0.61781970
#> [19] 0.78036609 0.35761118 0.67565072 0.32760766 0.47069472 0.32760766
#> [25] 0.88242162 0.01010366 0.08152929 0.59859421 0.37785520 0.42941333
#> [31] 0.15755794 0.59859421 0.19093136 0.54002393 0.61781970 0.75243371
#> [37] 0.48096941 0.91933974 0.98229020 0.94675123 0.77100970 0.78960353
#> [43] 0.73336368 0.39824885 0.23430228 0.64666132 0.08152929 0.24564803
#> [49] 0.13618200 0.11474124 0.51037264 0.03419766 0.53015153 0.41897040
#> [55] 0.92849519 0.26726285 0.50048355 0.32760766 0.69492041 0.91010350
#> [61] 0.57919333 0.86386305 0.92849519 0.10314212 0.99114290 0.40858377
#> [67] 0.44998129 0.69492041 0.42941333 0.54995703 0.31754103 0.75243371
#> [73] 0.89168033 0.89168033 0.28848597 0.17960003 0.19093136 0.44998129
#> [79] 0.72372523 0.61781970 0.28848597 0.55993929 0.83587254 0.87317867
#> [85] 0.68532718 0.78960353 0.28848597 0.27782950 0.94675123 0.04647650
#> [91] 0.81730410 0.78960353 0.19093136 0.04647650 0.65631440 0.96467257
#> [97] 0.19093136 0.11474124 0.13618200 0.96467257 0.58889296 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 106 42 100 49 24 170 32 86 117 55 15 40 96
#> 16.67 12.43 16.07 12.19 23.89 19.54 20.90 23.81 17.46 19.34 22.68 18.00 14.54
#> 155 24.1 56 86.1 85 154 170.1 39 105 41 105.1 10 24.2
#> 13.08 23.89 12.21 23.81 16.44 12.63 19.54 15.59 19.75 18.02 19.75 10.53 23.89
#> 168 181 58 108 15.1 181.1 175 30 85.1 123 40.1 187 91
#> 23.72 16.46 19.34 18.29 22.68 16.46 21.91 17.43 16.44 13.00 18.00 9.92 5.33
#> 70 14 177 60 76 197 79 168.1 139 92 69 110 78
#> 7.38 12.89 12.53 13.15 19.22 21.60 16.23 23.72 21.49 22.92 23.23 17.56 23.88
#> 111 88 16 128 184 105.2 157 101 171 43 16.1 164 127
#> 17.45 18.37 8.71 20.35 17.77 19.75 15.10 9.97 16.57 12.10 8.71 23.60 3.53
#> 179 51 157.1 108.1 23 166 123.1 93 93.1 158 194 175.1 51.1
#> 18.63 18.23 15.10 18.29 16.92 19.98 13.00 10.33 10.33 20.14 22.40 21.91 18.23
#> 13 85.2 158.1 106.1 56.1 107 29 177.1 158.2 150 70.1 86.2 42.1
#> 14.34 16.44 20.14 16.67 12.21 11.18 15.45 12.53 20.14 20.33 7.38 23.81 12.43
#> 177.2 175.2 86.3 188 25 175.3 69.1 92.1 25.1 130 65 112 185
#> 12.53 21.91 23.81 16.16 6.32 21.91 23.23 22.92 6.32 16.47 24.00 24.00 24.00
#> 80 191 20 46 131 47 178 67 3 80.1 71 19 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 33 75 135 196 80.2 151 116 178.1 84 131.1 131.2 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 82 17 165 118 75.1 34 80.3 122 161 173 160 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 152 182 126 156 141 34.1 118.1 2 53 148 121 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 200 152.1 146 176.1 143 71.1 2.1 119 198 21 95.1 71.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 67.2 121.1 48 131.3 47.1 17.1 2.2 116.2 160.1 165.1 126.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 19.1 161.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 5.519055e-06 4.522669e-01 -2.113761e-01
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.32108486 0.01117703 -0.75677154
#> grade_iii, Cure model
#> 0.67672595
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 32 20.90 1 37 1 0
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 197 21.60 1 69 1 0
#> 157 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 140 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 23 16.92 1 61 0 0
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 128 20.35 1 35 0 1
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 49 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 8 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 55.1 19.34 1 69 0 1
#> 97 19.14 1 65 0 1
#> 117 17.46 1 26 0 1
#> 117.1 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 117.2 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 85 16.44 1 36 0 0
#> 105 19.75 1 60 0 0
#> 77 7.27 1 67 0 1
#> 16 8.71 1 71 0 1
#> 100 16.07 1 60 0 0
#> 23.1 16.92 1 61 0 0
#> 97.1 19.14 1 65 0 1
#> 8.1 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 170 19.54 1 43 0 1
#> 13 14.34 1 54 0 1
#> 49.1 12.19 1 48 1 0
#> 16.1 8.71 1 71 0 1
#> 127 3.53 1 62 0 1
#> 93.1 10.33 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 133.1 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 86.1 23.81 1 58 0 1
#> 23.2 16.92 1 61 0 0
#> 91 5.33 1 61 0 1
#> 32.1 20.90 1 37 1 0
#> 108 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 16.2 8.71 1 71 0 1
#> 184 17.77 1 38 0 0
#> 133.2 14.65 1 57 0 0
#> 23.3 16.92 1 61 0 0
#> 155 13.08 1 26 0 0
#> 50 10.02 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 25.1 6.32 1 34 1 0
#> 49.2 12.19 1 48 1 0
#> 61 10.12 1 36 0 1
#> 128.1 20.35 1 35 0 1
#> 99 21.19 1 38 0 1
#> 49.3 12.19 1 48 1 0
#> 60.1 13.15 1 38 1 0
#> 136.1 21.83 1 43 0 1
#> 158 20.14 1 74 1 0
#> 42.1 12.43 1 49 0 1
#> 157.1 15.10 1 47 0 0
#> 49.4 12.19 1 48 1 0
#> 36.1 21.19 1 48 0 1
#> 155.1 13.08 1 26 0 0
#> 23.4 16.92 1 61 0 0
#> 77.1 7.27 1 67 0 1
#> 30 17.43 1 78 0 0
#> 56 12.21 1 60 0 0
#> 125 15.65 1 67 1 0
#> 99.1 21.19 1 38 0 1
#> 187 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 24 23.89 1 38 0 0
#> 187.1 9.92 1 39 1 0
#> 59.1 10.16 1 NA 1 0
#> 128.2 20.35 1 35 0 1
#> 79 16.23 1 54 1 0
#> 159 10.55 1 50 0 1
#> 190 20.81 1 42 1 0
#> 183 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 194.1 22.40 1 38 0 1
#> 42.2 12.43 1 49 0 1
#> 127.1 3.53 1 62 0 1
#> 10.1 10.53 1 34 0 0
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 70 7.38 1 30 1 0
#> 56.1 12.21 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 58 19.34 1 39 0 0
#> 23.5 16.92 1 61 0 0
#> 194.2 22.40 1 38 0 1
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 131 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 22 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 131.1 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 22.2 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 173.1 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 82 24.00 0 34 0 0
#> 71 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 126 24.00 0 48 0 0
#> 98.1 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 135.1 24.00 0 58 1 0
#> 62 24.00 0 71 0 0
#> 156.1 24.00 0 50 1 0
#> 28.1 24.00 0 67 1 0
#> 34 24.00 0 36 0 0
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 138 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 74 24.00 0 43 0 1
#> 27.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 115 24.00 0 NA 1 0
#> 118.1 24.00 0 44 1 0
#> 95.2 24.00 0 68 0 1
#> 71.1 24.00 0 51 0 0
#> 135.2 24.00 0 58 1 0
#> 12.1 24.00 0 63 0 0
#> 11 24.00 0 42 0 1
#> 95.3 24.00 0 68 0 1
#> 98.2 24.00 0 34 1 0
#> 27.2 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 11.2 24.00 0 42 0 1
#> 135.3 24.00 0 58 1 0
#> 121 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 3.1 24.00 0 31 1 0
#> 31.2 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 173.2 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 146.1 24.00 0 63 1 0
#> 156.2 24.00 0 50 1 0
#> 146.2 24.00 0 63 1 0
#> 147.1 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.321 NA NA NA
#> 2 age, Cure model 0.0112 NA NA NA
#> 3 grade_ii, Cure model -0.757 NA NA NA
#> 4 grade_iii, Cure model 0.677 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00000552 NA NA NA
#> 2 grade_ii, Survival model 0.452 NA NA NA
#> 3 grade_iii, Survival model -0.211 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.32108 0.01118 -0.75677 0.67673
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 248.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.32108486 0.01117703 -0.75677154 0.67672595
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 5.519055e-06 4.522669e-01 -2.113761e-01
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.489284818 0.403138145 0.163655578 0.663310209 0.364463260 0.094226718
#> [7] 0.114866744 0.558344522 0.606020774 0.013533203 0.819193161 0.855882805
#> [13] 0.672773183 0.125143712 0.432807728 0.499223461 0.828357574 0.192386012
#> [19] 0.955286272 0.403138145 0.738330383 0.258607383 0.315867878 0.345056820
#> [25] 0.258607383 0.286734757 0.374215868 0.374215868 0.577511035 0.801005361
#> [31] 0.038276683 0.374215868 0.066145302 0.691547930 0.509199904 0.239478600
#> [37] 0.937268740 0.901305137 0.529044207 0.432807728 0.286734757 0.315867878
#> [43] 0.625421193 0.249008012 0.615706442 0.738330383 0.901305137 0.982080947
#> [49] 0.828357574 0.038276683 0.577511035 0.229949113 0.013533203 0.432807728
#> [55] 0.973111459 0.163655578 0.335194902 0.682160582 0.901305137 0.354760059
#> [61] 0.577511035 0.432807728 0.644365721 0.056066821 0.955286272 0.738330383
#> [67] 0.846661670 0.192386012 0.125143712 0.738330383 0.625421193 0.094226718
#> [73] 0.220419578 0.691547930 0.558344522 0.738330383 0.125143712 0.644365721
#> [79] 0.432807728 0.937268740 0.422839595 0.719543581 0.538912044 0.125143712
#> [85] 0.874230569 0.548677527 0.004979631 0.874230569 0.192386012 0.519176314
#> [91] 0.782817502 0.182828586 0.892284533 0.029037901 0.066145302 0.691547930
#> [97] 0.982080947 0.801005361 0.306051926 0.865047421 0.928249406 0.719543581
#> [103] 0.782817502 0.258607383 0.432807728 0.066145302 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 171 111 32 123 110 136 197 157 57 86 52 145 140
#> 16.57 17.45 20.90 13.00 17.56 21.83 21.60 15.10 14.46 23.81 10.42 10.07 12.68
#> 36 23 130 93 128 25 111.1 49 55 8 134 55.1 97
#> 21.19 16.92 16.47 10.33 20.35 6.32 17.45 12.19 19.34 18.43 17.81 19.34 19.14
#> 117 117.1 133 10 164 117.2 194 42 85 105 77 16 100
#> 17.46 17.46 14.65 10.53 23.60 17.46 22.40 12.43 16.44 19.75 7.27 8.71 16.07
#> 23.1 97.1 8.1 60 170 13 49.1 16.1 127 93.1 164.1 133.1 166
#> 16.92 19.14 18.43 13.15 19.54 14.34 12.19 8.71 3.53 10.33 23.60 14.65 19.98
#> 86.1 23.2 91 32.1 108 177 16.2 184 133.2 23.3 155 69 25.1
#> 23.81 16.92 5.33 20.90 18.29 12.53 8.71 17.77 14.65 16.92 13.08 23.23 6.32
#> 49.2 61 128.1 99 49.3 60.1 136.1 158 42.1 157.1 49.4 36.1 155.1
#> 12.19 10.12 20.35 21.19 12.19 13.15 21.83 20.14 12.43 15.10 12.19 21.19 13.08
#> 23.4 77.1 30 56 125 99.1 187 29 24 187.1 128.2 79 159
#> 16.92 7.27 17.43 12.21 15.65 21.19 9.92 15.45 23.89 9.92 20.35 16.23 10.55
#> 190 183 168 194.1 42.2 127.1 10.1 179 101 70 56.1 159.1 58
#> 20.81 9.24 23.72 22.40 12.43 3.53 10.53 18.63 9.97 7.38 12.21 10.55 19.34
#> 23.5 194.2 94 173 147 131 174 22 118 31 35 176 135
#> 16.92 22.40 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 156 53 196 95 142 38 172 22.1 131.1 3 83 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.2 75 173.1 104 104.1 98 82 71 178 126 98.1 28 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 135.1 62 156.1 28.1 34 27 186 31.1 19 138 95.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 74 27.1 12 141 1 185 67 118.1 95.2 71.1 135.2 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 95.3 98.2 27.2 151 9 11.1 146 11.2 135.3 121 144 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.2 143 116.1 21 173.2 46 2 146.1 156.2 146.2 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006422688 1.522470292 0.969507806
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.75986097 0.03425508 0.15591787
#> grade_iii, Cure model
#> 1.22493968
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 107 11.18 1 54 1 0
#> 78 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 57 14.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 36 21.19 1 48 0 1
#> 96 14.54 1 33 0 1
#> 105 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 169 22.41 1 46 0 0
#> 13 14.34 1 54 0 1
#> 49 12.19 1 48 1 0
#> 101 9.97 1 10 0 1
#> 15 22.68 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 99 21.19 1 38 0 1
#> 70 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 169.1 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 61 10.12 1 36 0 1
#> 171 16.57 1 41 0 1
#> 155 13.08 1 26 0 0
#> 50 10.02 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 125 15.65 1 67 1 0
#> 169.2 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 179 18.63 1 42 0 0
#> 168 23.72 1 70 0 0
#> 130.1 16.47 1 53 0 1
#> 23 16.92 1 61 0 0
#> 188 16.16 1 46 0 1
#> 93 10.33 1 52 0 1
#> 149 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 39 15.59 1 37 0 1
#> 6 15.64 1 39 0 0
#> 149.1 8.37 1 33 1 0
#> 66 22.13 1 53 0 0
#> 36.1 21.19 1 48 0 1
#> 24 23.89 1 38 0 0
#> 190 20.81 1 42 1 0
#> 23.1 16.92 1 61 0 0
#> 171.1 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 92 22.92 1 47 0 1
#> 90.1 20.94 1 50 0 1
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 149.2 8.37 1 33 1 0
#> 4 17.64 1 NA 0 1
#> 188.1 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 134.1 17.81 1 47 1 0
#> 41.1 18.02 1 40 1 0
#> 57.1 14.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 85 16.44 1 36 0 0
#> 107.1 11.18 1 54 1 0
#> 6.1 15.64 1 39 0 0
#> 175 21.91 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 78.2 23.88 1 43 0 0
#> 169.3 22.41 1 46 0 0
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 88 18.37 1 47 0 0
#> 100 16.07 1 60 0 0
#> 127.1 3.53 1 62 0 1
#> 192 16.44 1 31 1 0
#> 177.1 12.53 1 75 0 0
#> 150.1 20.33 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 124 9.73 1 NA 1 0
#> 175.2 21.91 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 50.1 10.02 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 89 11.44 1 NA 0 0
#> 195.1 11.76 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 117 17.46 1 26 0 1
#> 125.1 15.65 1 67 1 0
#> 93.1 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 76 19.22 1 54 0 1
#> 124.1 9.73 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 79.1 16.23 1 54 1 0
#> 158 20.14 1 74 1 0
#> 23.2 16.92 1 61 0 0
#> 30 17.43 1 78 0 0
#> 90.2 20.94 1 50 0 1
#> 195.2 11.76 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 125.2 15.65 1 67 1 0
#> 79.2 16.23 1 54 1 0
#> 51 18.23 1 83 0 1
#> 151 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 3 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 143 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 3.1 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 83.1 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 141 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 104 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 34.1 24.00 0 36 0 0
#> 138.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 3.2 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 54 24.00 0 53 1 0
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 75.1 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 11.1 24.00 0 42 0 1
#> 196 24.00 0 19 0 0
#> 173 24.00 0 19 0 1
#> 47 24.00 0 38 0 1
#> 21.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 75.2 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 27.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 104.1 24.00 0 50 1 0
#> 34.2 24.00 0 36 0 0
#> 143.1 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 102 24.00 0 49 0 0
#> 27.2 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 102.1 24.00 0 49 0 0
#> 67 24.00 0 25 0 0
#> 12.1 24.00 0 63 0 0
#> 119.1 24.00 0 17 0 0
#> 115.1 24.00 0 NA 1 0
#> 67.1 24.00 0 25 0 0
#> 87 24.00 0 27 0 0
#> 131 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 182.2 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 182.3 24.00 0 35 0 0
#> 186.1 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#> 94 24.00 0 51 0 1
#> 31 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 135.1 24.00 0 58 1 0
#> 196.2 24.00 0 19 0 0
#> 3.3 24.00 0 31 1 0
#> 34.3 24.00 0 36 0 0
#> 161 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.76 NA NA NA
#> 2 age, Cure model 0.0343 NA NA NA
#> 3 grade_ii, Cure model 0.156 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00642 NA NA NA
#> 2 grade_ii, Survival model 1.52 NA NA NA
#> 3 grade_iii, Survival model 0.970 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.75986 0.03426 0.15592 1.22494
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 237.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.75986097 0.03425508 0.15591787 1.22493968
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006422688 1.522470292 0.969507806
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90700804 0.03674495 0.53174195 0.83203730 0.25597679 0.39028261
#> [7] 0.82546119 0.52102269 0.61254996 0.18906709 0.84493952 0.90095639
#> [13] 0.94181915 0.17145212 0.03674495 0.11855561 0.15430563 0.39028261
#> [19] 0.97975488 0.73527607 0.81882518 0.18906709 0.42960172 0.37516559
#> [25] 0.91872197 0.93608122 0.68753610 0.86394364 0.70381089 0.34292222
#> [31] 0.77828643 0.18906709 0.88867099 0.56296462 0.08021078 0.70381089
#> [37] 0.66266856 0.75689835 0.92456363 0.96410057 0.48846059 0.81206877
#> [43] 0.79849078 0.96410057 0.27330403 0.39028261 0.01025307 0.47751032
#> [49] 0.66266856 0.68753610 0.85767376 0.59385855 0.13752641 0.42960172
#> [55] 0.95305900 0.94181915 0.96410057 0.75689835 0.87022053 0.61254996
#> [61] 0.59385855 0.83203730 0.84493952 0.98991732 0.87636312 0.71976261
#> [67] 0.90700804 0.79849078 0.29095439 0.01025307 0.03674495 0.18906709
#> [73] 0.89480695 0.57326344 0.77112085 0.98991732 0.71976261 0.87636312
#> [79] 0.48846059 0.29095439 0.29095439 0.34292222 0.61254996 0.97975488
#> [85] 0.63764897 0.77828643 0.92456363 0.55271016 0.95861127 0.54231359
#> [91] 0.65437567 0.08021078 0.73527607 0.51037350 0.66266856 0.64599098
#> [97] 0.42960172 0.46589418 0.77828643 0.73527607 0.58361070 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 107 78 55 57 194 36 96 105 134 169 13 49 101
#> 11.18 23.88 19.34 14.46 22.40 21.19 14.54 19.75 17.81 22.41 14.34 12.19 9.97
#> 15 78.1 164 113 99 70 79 167 169.1 90 139 159 61
#> 22.68 23.88 23.60 22.86 21.19 7.38 16.23 15.55 22.41 20.94 21.49 10.55 10.12
#> 171 155 130 136 125 169.2 42 179 168 130.1 23 188 93
#> 16.57 13.08 16.47 21.83 15.65 22.41 12.43 18.63 23.72 16.47 16.92 16.16 10.33
#> 149 150 39 6 149.1 66 36.1 24 190 23.1 171.1 60 41
#> 8.37 20.33 15.59 15.64 8.37 22.13 21.19 23.89 20.81 16.92 16.57 13.15 18.02
#> 92 90.1 187 101.1 149.2 188.1 154 134.1 41.1 57.1 13.1 127 177
#> 22.92 20.94 9.92 9.97 8.37 16.16 12.63 17.81 18.02 14.46 14.34 3.53 12.53
#> 85 107.1 6.1 175 24.1 78.2 169.3 56 88 100 127.1 192 177.1
#> 16.44 11.18 15.64 21.91 23.89 23.88 22.41 12.21 18.37 16.07 3.53 16.44 12.53
#> 150.1 175.1 175.2 136.1 134.2 70.1 117 125.1 93.1 97 183 76 45
#> 20.33 21.91 21.91 21.83 17.81 7.38 17.46 15.65 10.33 19.14 9.24 19.22 17.42
#> 168.1 79.1 158 23.2 30 90.2 32 125.2 79.2 51 151 21 174
#> 23.72 16.23 20.14 16.92 17.43 20.94 20.90 15.65 16.23 18.23 24.00 24.00 24.00
#> 12 46 3 83 11 143 162 116 3.1 151.1 182 83.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 160 75 138 27 17 71 34 141 182.1 103 104 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 138.1 84 109 163 82 3.2 7 54 193 186 75.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 126 11.1 196 173 47 21.1 191 75.2 132 119 27.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 34.2 143.1 196.1 102 27.2 33 102.1 67 12.1 119.1 67.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 7.1 182.2 121 182.3 186.1 80 132.1 94 31 172 156 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 196.2 3.3 34.3 161
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004447739 0.502396241 0.004660948
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.6569223 0.0297834 -0.1301515
#> grade_iii, Cure model
#> 1.4553295
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 77 7.27 1 67 0 1
#> 124 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 133 14.65 1 57 0 0
#> 93 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 175 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 32 20.90 1 37 1 0
#> 181 16.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 157 15.10 1 47 0 0
#> 149 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 124.1 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 184 17.77 1 38 0 0
#> 110 17.56 1 65 0 1
#> 133.1 14.65 1 57 0 0
#> 88.1 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 90 20.94 1 50 0 1
#> 14 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 128 20.35 1 35 0 1
#> 29 15.45 1 68 1 0
#> 70 7.38 1 30 1 0
#> 5 16.43 1 51 0 1
#> 61 10.12 1 36 0 1
#> 180 14.82 1 37 0 0
#> 128.1 20.35 1 35 0 1
#> 99.1 21.19 1 38 0 1
#> 108 18.29 1 39 0 1
#> 42 12.43 1 49 0 1
#> 45 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 89 11.44 1 NA 0 0
#> 177 12.53 1 75 0 0
#> 58 19.34 1 39 0 0
#> 183 9.24 1 67 1 0
#> 105.1 19.75 1 60 0 0
#> 159 10.55 1 50 0 1
#> 99.2 21.19 1 38 0 1
#> 70.1 7.38 1 30 1 0
#> 171 16.57 1 41 0 1
#> 155.1 13.08 1 26 0 0
#> 105.2 19.75 1 60 0 0
#> 99.3 21.19 1 38 0 1
#> 124.2 9.73 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 114 13.68 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 166 19.98 1 48 0 0
#> 125 15.65 1 67 1 0
#> 187 9.92 1 39 1 0
#> 184.1 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 50.1 10.02 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 10 10.53 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 188.2 16.16 1 46 0 1
#> 105.3 19.75 1 60 0 0
#> 45.1 17.42 1 54 0 1
#> 85 16.44 1 36 0 0
#> 110.1 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 88.2 18.37 1 47 0 0
#> 136 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 114.1 13.68 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 30.1 17.43 1 78 0 0
#> 177.2 12.53 1 75 0 0
#> 184.2 17.77 1 38 0 0
#> 68 20.62 1 44 0 0
#> 179 18.63 1 42 0 0
#> 153 21.33 1 55 1 0
#> 139 21.49 1 63 1 0
#> 45.2 17.42 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 42.1 12.43 1 49 0 1
#> 13 14.34 1 54 0 1
#> 125.1 15.65 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 52.1 10.42 1 52 0 1
#> 169 22.41 1 46 0 0
#> 189.1 10.51 1 NA 1 0
#> 42.2 12.43 1 49 0 1
#> 16 8.71 1 71 0 1
#> 77.1 7.27 1 67 0 1
#> 52.2 10.42 1 52 0 1
#> 164 23.60 1 76 0 1
#> 10.1 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 69.2 23.23 1 25 0 1
#> 199 19.81 1 NA 0 1
#> 184.3 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 5.1 16.43 1 51 0 1
#> 194 22.40 1 38 0 1
#> 101 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 133.2 14.65 1 57 0 0
#> 56 12.21 1 60 0 0
#> 87 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 112 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 196.1 24.00 0 19 0 0
#> 22 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 146 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 67 24.00 0 25 0 0
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 144 24.00 0 28 0 1
#> 109 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 143 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 75 24.00 0 21 1 0
#> 47.1 24.00 0 38 0 1
#> 109.1 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 47.2 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 191 24.00 0 60 0 1
#> 200 24.00 0 64 0 0
#> 1.1 24.00 0 23 1 0
#> 131.1 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 165.1 24.00 0 47 0 0
#> 161.1 24.00 0 45 0 0
#> 112.1 24.00 0 61 0 0
#> 19 24.00 0 57 0 1
#> 46 24.00 0 71 0 0
#> 131.2 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 132.1 24.00 0 55 0 0
#> 141.1 24.00 0 44 1 0
#> 1.2 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 82 24.00 0 34 0 0
#> 143.1 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 162.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 2.2 24.00 0 9 0 0
#> 138 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 182 24.00 0 35 0 0
#> 74.1 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 162.2 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 98.1 24.00 0 34 1 0
#> 109.2 24.00 0 48 0 0
#> 84.2 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.66 NA NA NA
#> 2 age, Cure model 0.0298 NA NA NA
#> 3 grade_ii, Cure model -0.130 NA NA NA
#> 4 grade_iii, Cure model 1.46 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00445 NA NA NA
#> 2 grade_ii, Survival model 0.502 NA NA NA
#> 3 grade_iii, Survival model 0.00466 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.65692 0.02978 -0.13015 1.45533
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 229 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.6569223 0.0297834 -0.1301515 1.4553295
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004447739 0.502396241 0.004660948
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.35686588 0.97842959 0.22774209 0.73230472 0.90395214 0.69150302
#> [7] 0.17278924 0.65717676 0.30330840 0.59529588 0.06803164 0.42654605
#> [13] 0.71607944 0.95663039 0.22774209 0.63103304 0.63103304 0.40638565
#> [19] 0.46537752 0.50292800 0.73230472 0.42654605 0.52182201 0.28107611
#> [25] 0.78797591 0.77212317 0.32510731 0.69988755 0.96398049 0.61330927
#> [31] 0.91159898 0.72420021 0.32510731 0.22774209 0.45554136 0.81929837
#> [37] 0.54991410 0.99280368 0.79593468 0.39621023 0.93443850 0.35686588
#> [43] 0.85804053 0.22774209 0.96398049 0.58624638 0.77212317 0.35686588
#> [49] 0.22774209 0.79593468 0.53133391 0.75612456 0.34622128 0.67460756
#> [55] 0.92686653 0.46537752 0.12695879 0.69988755 0.86578307 0.65717676
#> [61] 0.63103304 0.35686588 0.54991410 0.60431423 0.50292800 0.88115424
#> [67] 0.42654605 0.18749095 0.02280586 0.53133391 0.79593468 0.46537752
#> [73] 0.31424869 0.41649090 0.21527344 0.20194802 0.54991410 0.93443850
#> [79] 0.28107611 0.81929837 0.76413548 0.67460756 0.06803164 0.88115424
#> [85] 0.14257795 0.81929837 0.94922832 0.97842959 0.88115424 0.04744072
#> [91] 0.86578307 0.57716806 0.06803164 0.46537752 0.85028014 0.61330927
#> [97] 0.15782004 0.91923435 0.11087182 0.73230472 0.84249717 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 105 77 36 133 93 167 175 26 32 181 69 88 157
#> 19.75 7.27 21.19 14.65 10.33 15.55 21.91 15.77 20.90 16.46 23.23 18.37 15.10
#> 149 99 188 188.1 76 184 110 133.1 88.1 117 90 14 155
#> 8.37 21.19 16.16 16.16 19.22 17.77 17.56 14.65 18.37 17.46 20.94 12.89 13.08
#> 128 29 70 5 61 180 128.1 99.1 108 42 45 127 177
#> 20.35 15.45 7.38 16.43 10.12 14.82 20.35 21.19 18.29 12.43 17.42 3.53 12.53
#> 58 183 105.1 159 99.2 70.1 171 155.1 105.2 99.3 177.1 30 96
#> 19.34 9.24 19.75 10.55 21.19 7.38 16.57 13.08 19.75 21.19 12.53 17.43 14.54
#> 166 125 187 184.1 15 29.1 10 26.1 188.2 105.3 45.1 85 110.1
#> 19.98 15.65 9.92 17.77 22.68 15.45 10.53 15.77 16.16 19.75 17.42 16.44 17.56
#> 52 88.2 136 168 30.1 177.2 184.2 68 179 153 139 45.2 183.1
#> 10.42 18.37 21.83 23.72 17.43 12.53 17.77 20.62 18.63 21.33 21.49 17.42 9.24
#> 90.1 42.1 13 125.1 69.1 52.1 169 42.2 16 77.1 52.2 164 10.1
#> 20.94 12.43 14.34 15.65 23.23 10.42 22.41 12.43 8.71 7.27 10.42 23.60 10.53
#> 106 69.2 184.3 43 5.1 194 101 92 133.2 56 87 137 84
#> 16.67 23.23 17.77 12.10 16.43 22.40 9.97 22.92 14.65 12.21 24.00 24.00 24.00
#> 47 95 34 163 132 141 196 112 142 174 196.1 22 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 35 2 67 83 135 98 144 109 72 143 35.1 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 186 75 47.1 109.1 20 1 151 121 83.1 198 131 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 21 47.2 151.1 191 200 1.1 131.1 31 9 67.1 165.1 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 19 46 131.2 54 132.1 141.1 1.2 33 34.1 44 162 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 48 74 162.1 103 2.1 144.1 2.2 138 182 74.1 172 162.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 98.1 109.2 84.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005533265 0.5673417020 0.0204185862
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.24390386 0.02657256 -0.17388670
#> grade_iii, Cure model
#> 1.07337526
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 69 23.23 1 25 0 1
#> 93 10.33 1 52 0 1
#> 125 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 164 23.60 1 76 0 1
#> 37 12.52 1 57 1 0
#> 199 19.81 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 10 10.53 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 66 22.13 1 53 0 0
#> 32 20.90 1 37 1 0
#> 169 22.41 1 46 0 0
#> 4 17.64 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 88 18.37 1 47 0 0
#> 70 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 29 15.45 1 68 1 0
#> 24 23.89 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 42 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 8 18.43 1 32 0 0
#> 164.1 23.60 1 76 0 1
#> 157 15.10 1 47 0 0
#> 89.1 11.44 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 68 20.62 1 44 0 0
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 110 17.56 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 199.1 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 149.1 8.37 1 33 1 0
#> 18 15.21 1 49 1 0
#> 14 12.89 1 21 0 0
#> 29.1 15.45 1 68 1 0
#> 130 16.47 1 53 0 1
#> 86 23.81 1 58 0 1
#> 179 18.63 1 42 0 0
#> 199.2 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 199.3 19.81 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 89.2 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 52 10.42 1 52 0 1
#> 199.4 19.81 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 86.1 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 169.1 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 86.2 23.81 1 58 0 1
#> 37.1 12.52 1 57 1 0
#> 130.1 16.47 1 53 0 1
#> 133 14.65 1 57 0 0
#> 125.2 15.65 1 67 1 0
#> 177.1 12.53 1 75 0 0
#> 39 15.59 1 37 0 1
#> 15 22.68 1 48 0 0
#> 106 16.67 1 49 1 0
#> 180 14.82 1 37 0 0
#> 124 9.73 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 79.1 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 60.1 13.15 1 38 1 0
#> 66.1 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 5 16.43 1 51 0 1
#> 81 14.06 1 34 0 0
#> 76 19.22 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 106.1 16.67 1 49 1 0
#> 63.1 22.77 1 31 1 0
#> 43 12.10 1 61 0 1
#> 114.1 13.68 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 188 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 199.5 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 105.1 19.75 1 60 0 0
#> 63.2 22.77 1 31 1 0
#> 10.1 10.53 1 34 0 0
#> 61 10.12 1 36 0 1
#> 145.1 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 14.1 12.89 1 21 0 0
#> 8.1 18.43 1 32 0 0
#> 37.2 12.52 1 57 1 0
#> 105.2 19.75 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 110.1 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 181.1 16.46 1 45 0 1
#> 195.1 11.76 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 8.2 18.43 1 32 0 0
#> 90.2 20.94 1 50 0 1
#> 29.2 15.45 1 68 1 0
#> 24.1 23.89 1 38 0 0
#> 118 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 7 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 200 24.00 0 64 0 0
#> 132 24.00 0 55 0 0
#> 116 24.00 0 58 0 1
#> 161 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 162 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 48 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 7.2 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 47 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 174.1 24.00 0 49 1 0
#> 138.1 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 9.1 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 72 24.00 0 40 0 1
#> 1.1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 72.1 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 34.1 24.00 0 36 0 0
#> 38 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 75.1 24.00 0 21 1 0
#> 9.2 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 46.1 24.00 0 71 0 0
#> 38.1 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 102 24.00 0 49 0 0
#> 73.1 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 126.1 24.00 0 48 0 0
#> 162.2 24.00 0 51 0 0
#> 12.2 24.00 0 63 0 0
#> 115.1 24.00 0 NA 1 0
#> 27.1 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 7.3 24.00 0 37 1 0
#> 9.3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 185.1 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 87.1 24.00 0 27 0 0
#> 161.1 24.00 0 45 0 0
#> 1.2 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 34.2 24.00 0 36 0 0
#> 121 24.00 0 57 1 0
#> 174.2 24.00 0 49 1 0
#> 174.3 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.24 NA NA NA
#> 2 age, Cure model 0.0266 NA NA NA
#> 3 grade_ii, Cure model -0.174 NA NA NA
#> 4 grade_iii, Cure model 1.07 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000553 NA NA NA
#> 2 grade_ii, Survival model 0.567 NA NA NA
#> 3 grade_iii, Survival model 0.0204 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.24390 0.02657 -0.17389 1.07338
#>
#> Degrees of Freedom: 179 Total (i.e. Null); 176 Residual
#> Null Deviance: 248.7
#> Residual Deviance: 232 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.24390386 0.02657256 -0.17388670 1.07337526
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005533265 0.5673417020 0.0204185862
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.11370623 0.88870179 0.58533829 0.55510494 0.08502563 0.80911606
#> [7] 0.44013150 0.86221910 0.26751059 0.19748096 0.31111600 0.17429217
#> [13] 0.52407408 0.93249021 0.47210055 0.41847355 0.94953502 0.33293426
#> [19] 0.62397290 0.01664965 0.98320417 0.83559078 0.23272658 0.38656184
#> [25] 0.08502563 0.66129745 0.12907624 0.32202067 0.27873877 0.90641876
#> [31] 0.45086787 0.27873877 0.73601373 0.93249021 0.65193687 0.76351186
#> [37] 0.62397290 0.50345791 0.04623044 0.37563450 0.96635803 0.58533829
#> [43] 0.87984401 0.70801184 0.04623044 0.79094486 0.17429217 0.97480769
#> [49] 0.04623044 0.80911606 0.50345791 0.68926917 0.58533829 0.79094486
#> [55] 0.61419819 0.16232798 0.48284935 0.67066144 0.67066144 0.55510494
#> [61] 0.69864064 0.24470358 0.73601373 0.19748096 0.84451121 0.54469397
#> [67] 0.71738360 0.36471448 0.94953502 0.48284935 0.12907624 0.85336455
#> [73] 0.25628536 0.42940059 0.57520035 0.22075180 0.78181506 0.33293426
#> [79] 0.12907624 0.86221910 0.89756030 0.90641876 0.99160159 0.76351186
#> [85] 0.38656184 0.80911606 0.33293426 0.71738360 0.45086787 0.92381190
#> [91] 0.52407408 0.75430732 0.38656184 0.27873877 0.62397290 0.01664965
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 69 93 125 79 164 37 184 10 36 66 32 169 181
#> 23.23 10.33 15.65 16.23 23.60 12.52 17.77 10.53 21.19 22.13 20.90 22.41 16.46
#> 149 30 88 70 105 29 24 91 42 136 8 164.1 157
#> 8.37 17.43 18.37 7.38 19.75 15.45 23.89 5.33 12.43 21.83 18.43 23.60 15.10
#> 63 68 90 145 110 90.1 60 149.1 18 14 29.1 130 86
#> 22.77 20.62 20.94 10.07 17.56 20.94 13.15 8.37 15.21 12.89 15.45 16.47 23.81
#> 179 77 125.1 52 57 86.1 177 169.1 25 86.2 37.1 130.1 133
#> 18.63 7.27 15.65 10.42 14.46 23.81 12.53 22.41 6.32 23.81 12.52 16.47 14.65
#> 125.2 177.1 39 15 106 180 180.1 79.1 96 197 60.1 66.1 49
#> 15.65 12.53 15.59 22.68 16.67 14.82 14.82 16.23 14.54 21.60 13.15 22.13 12.19
#> 5 81 76 70.1 106.1 63.1 43 139 134 188 175 140 105.1
#> 16.43 14.06 19.22 7.38 16.67 22.77 12.10 21.49 17.81 16.16 21.91 12.68 19.75
#> 63.2 10.1 61 145.1 127 14.1 8.1 37.2 105.2 81.1 110.1 187 181.1
#> 22.77 10.53 10.12 10.07 3.53 12.89 18.43 12.52 19.75 14.06 17.56 9.92 16.46
#> 155 8.2 90.2 29.2 24.1 118 75 103 7 109 9 1 198
#> 13.08 18.43 20.94 15.45 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 132 116 161 46 182 162 67 138 174 186 35 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 7.2 27 126 87 47 34 174.1 138.1 138.2 162.1 12 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 103.1 44 72 1.1 118.1 84 72.1 160 31 185 176 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 34.1 38 109.1 75.1 9.2 3.1 12.1 46.1 38.1 83 53 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 126.1 162.2 12.2 27.1 143 53.1 7.3 9.3 142 119 185.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 161.1 1.2 65 65.1 34.2 121 174.2 174.3 54 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006489781 0.209806230 0.376100454
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.0718265799 0.0002751754 0.1543568209
#> grade_iii, Cure model
#> 0.5589178207
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 93 10.33 1 52 0 1
#> 68 20.62 1 44 0 0
#> 108 18.29 1 39 0 1
#> 81 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 113 22.86 1 34 0 0
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 78 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 30 17.43 1 78 0 0
#> 187 9.92 1 39 1 0
#> 16.1 8.71 1 71 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 50.1 10.02 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 79 16.23 1 54 1 0
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 70 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 70.1 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 101 9.97 1 10 0 1
#> 128 20.35 1 35 0 1
#> 167.1 15.55 1 56 1 0
#> 129 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 14 12.89 1 21 0 0
#> 8 18.43 1 32 0 0
#> 13 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 190 20.81 1 42 1 0
#> 100 16.07 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 69 23.23 1 25 0 1
#> 199.1 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 197 21.60 1 69 1 0
#> 66.1 22.13 1 53 0 0
#> 69.1 23.23 1 25 0 1
#> 50.2 10.02 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 134 17.81 1 47 1 0
#> 139.1 21.49 1 63 1 0
#> 76 19.22 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 15 22.68 1 48 0 0
#> 92 22.92 1 47 0 1
#> 5 16.43 1 51 0 1
#> 36 21.19 1 48 0 1
#> 81.1 14.06 1 34 0 0
#> 194 22.40 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 50.3 10.02 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 129.2 23.41 1 53 1 0
#> 70.2 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 10 10.53 1 34 0 0
#> 78.1 23.88 1 43 0 0
#> 76.2 19.22 1 54 0 1
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 158.1 20.14 1 74 1 0
#> 166 19.98 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 157.1 15.10 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 117.1 17.46 1 26 0 1
#> 16.2 8.71 1 71 0 1
#> 158.2 20.14 1 74 1 0
#> 127 3.53 1 62 0 1
#> 37.1 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 24 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 50.4 10.02 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 30.1 17.43 1 78 0 0
#> 63.1 22.77 1 31 1 0
#> 78.2 23.88 1 43 0 0
#> 40.1 18.00 1 28 1 0
#> 197.1 21.60 1 69 1 0
#> 145 10.07 1 65 1 0
#> 89.1 11.44 1 NA 0 0
#> 189.1 10.51 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 92.1 22.92 1 47 0 1
#> 180 14.82 1 37 0 0
#> 14.1 12.89 1 21 0 0
#> 45.1 17.42 1 54 0 1
#> 43 12.10 1 61 0 1
#> 14.2 12.89 1 21 0 0
#> 40.2 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 82 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 102 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 1.1 24.00 0 23 1 0
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 161 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 191.1 24.00 0 60 0 1
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 82.1 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 120 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 102.1 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 116 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 152 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 163.1 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 174 24.00 0 49 1 0
#> 75 24.00 0 21 1 0
#> 126.1 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 75.1 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 1.2 24.00 0 23 1 0
#> 191.2 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 80 24.00 0 41 0 0
#> 98.1 24.00 0 34 1 0
#> 73.1 24.00 0 NA 0 1
#> 95.1 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 132.1 24.00 0 55 0 0
#> 163.2 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 33.1 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 191.3 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 46.1 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 112.1 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 84 24.00 0 39 0 1
#> 132.2 24.00 0 55 0 0
#> 160.1 24.00 0 31 1 0
#> 33.2 24.00 0 53 0 0
#> 75.2 24.00 0 21 1 0
#> 120.1 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 103.1 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0718 NA NA NA
#> 2 age, Cure model 0.000275 NA NA NA
#> 3 grade_ii, Cure model 0.154 NA NA NA
#> 4 grade_iii, Cure model 0.559 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00649 NA NA NA
#> 2 grade_ii, Survival model 0.210 NA NA NA
#> 3 grade_iii, Survival model 0.376 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.0718266 0.0002752 0.1543568 0.5589178
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 251.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.0718265799 0.0002751754 0.1543568209 0.5589178207
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006489781 0.209806230 0.376100454
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91394254 0.47725535 0.60449262 0.82780649 0.57014162 0.27126482
#> [7] 0.94565046 0.53468589 0.08898050 0.69233171 0.76575523 0.67692871
#> [13] 0.93936579 0.94565046 0.38973956 0.32653996 0.32653996 0.72970654
#> [19] 0.90748653 0.71490142 0.42435636 0.77973276 0.96390614 0.96390614
#> [25] 0.75863320 0.93305627 0.48745143 0.76575523 0.15764616 0.88789500
#> [31] 0.36527672 0.87473418 0.80737552 0.84802584 0.58745828 0.82101744
#> [37] 0.28585328 0.49747393 0.46698677 0.73701471 0.15764616 0.20998386
#> [43] 0.74428855 0.40181291 0.36527672 0.20998386 0.86804952 0.64538131
#> [49] 0.42435636 0.54402206 0.58745828 0.57882024 0.31292038 0.24250158
#> [55] 0.72234297 0.44591923 0.82780649 0.35247568 0.54402206 0.80737552
#> [61] 0.15764616 0.96390614 0.98803669 0.61296532 0.90098233 0.08898050
#> [67] 0.54402206 0.66129125 0.78669560 0.49747393 0.52530254 0.84127459
#> [73] 0.78669560 0.62126636 0.66129125 0.94565046 0.49747393 0.99403955
#> [79] 0.87473418 0.45657630 0.70737728 0.04073034 0.75149186 0.98199108
#> [85] 0.67692871 0.28585328 0.08898050 0.62126636 0.40181291 0.92672302
#> [91] 0.64538131 0.24250158 0.80047307 0.84802584 0.69233171 0.89446653
#> [97] 0.84802584 0.62126636 0.92035141 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 93 68 108 81 97 113 16 58 78 45 167 30 187
#> 10.33 20.62 18.29 14.06 19.14 22.86 8.71 19.34 23.88 17.42 15.55 17.43 9.92
#> 16.1 136 169 169.1 79 52 130 139 29 70 70.1 6 101
#> 8.71 21.83 22.41 22.41 16.23 10.42 16.47 21.49 15.45 7.38 7.38 15.64 9.97
#> 128 167.1 129 49 66 37 133 14 8 13 63 158 190
#> 20.35 15.55 23.41 12.19 22.13 12.52 14.65 12.89 18.43 14.34 22.77 20.14 20.81
#> 100 129.1 69 26 197 66.1 69.1 140 134 139.1 76 8.1 179
#> 16.07 23.41 23.23 15.77 21.60 22.13 23.23 12.68 17.81 21.49 19.22 18.43 18.63
#> 15 92 5 36 81.1 194 76.1 133.1 129.2 70.2 91 51 10
#> 22.68 22.92 16.43 21.19 14.06 22.40 19.22 14.65 23.41 7.38 5.33 18.23 10.53
#> 78.1 76.2 117 157 158.1 166 155 157.1 40 117.1 16.2 158.2 127
#> 23.88 19.22 17.46 15.10 20.14 19.98 13.08 15.10 18.00 17.46 8.71 20.14 3.53
#> 37.1 90 23 24 125 25 30.1 63.1 78.2 40.1 197.1 145 134.1
#> 12.52 20.94 16.92 23.89 15.65 6.32 17.43 22.77 23.88 18.00 21.60 10.07 17.81
#> 92.1 180 14.1 45.1 43 14.2 40.2 61 82 138 46 1 102
#> 22.92 14.82 12.89 17.42 12.10 12.89 18.00 10.12 24.00 24.00 24.00 24.00 24.00
#> 196 31 1.1 191 132 198 161 44 178 191.1 135 104 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 82.1 72 200 120 9 53 102.1 109 3 98 95 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 33 64 185 7 71 148 116 35 185.1 147 152 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 104.1 163.1 112 174 75 126.1 75.1 160 1.2 191.2 67 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 95.1 172 142 132.1 163.2 11 186 33.1 144 141 191.3 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 121 17 112.1 103 84 132.2 160.1 33.2 75.2 120.1 122 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 62
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002830105 0.696791349 0.695823982
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.49937080 0.01178743 -0.05923753
#> grade_iii, Cure model
#> 0.57152132
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 68 20.62 1 44 0 0
#> 25 6.32 1 34 1 0
#> 8 18.43 1 32 0 0
#> 180 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 113 22.86 1 34 0 0
#> 6 15.64 1 39 0 0
#> 41 18.02 1 40 1 0
#> 97 19.14 1 65 0 1
#> 184 17.77 1 38 0 0
#> 6.1 15.64 1 39 0 0
#> 96 14.54 1 33 0 1
#> 184.1 17.77 1 38 0 0
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 85 16.44 1 36 0 0
#> 59 10.16 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 76 19.22 1 54 0 1
#> 187 9.92 1 39 1 0
#> 127 3.53 1 62 0 1
#> 45 17.42 1 54 0 1
#> 77 7.27 1 67 0 1
#> 78 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 29 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 23 16.92 1 61 0 0
#> 145 10.07 1 65 1 0
#> 157 15.10 1 47 0 0
#> 55 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 110 17.56 1 65 0 1
#> 187.1 9.92 1 39 1 0
#> 134 17.81 1 47 1 0
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 30 17.43 1 78 0 0
#> 63.1 22.77 1 31 1 0
#> 56 12.21 1 60 0 0
#> 159 10.55 1 50 0 1
#> 93 10.33 1 52 0 1
#> 150.1 20.33 1 48 0 0
#> 6.2 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 179 18.63 1 42 0 0
#> 58 19.34 1 39 0 0
#> 79 16.23 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 114 13.68 1 NA 0 0
#> 10 10.53 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 81 14.06 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 39 15.59 1 37 0 1
#> 68.1 20.62 1 44 0 0
#> 139.1 21.49 1 63 1 0
#> 25.1 6.32 1 34 1 0
#> 16 8.71 1 71 0 1
#> 85.1 16.44 1 36 0 0
#> 192 16.44 1 31 1 0
#> 25.2 6.32 1 34 1 0
#> 195.1 11.76 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 167 15.55 1 56 1 0
#> 24.1 23.89 1 38 0 0
#> 39.1 15.59 1 37 0 1
#> 190 20.81 1 42 1 0
#> 159.1 10.55 1 50 0 1
#> 15 22.68 1 48 0 0
#> 29.2 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 14 12.89 1 21 0 0
#> 13 14.34 1 54 0 1
#> 108 18.29 1 39 0 1
#> 169.1 22.41 1 46 0 0
#> 13.1 14.34 1 54 0 1
#> 159.2 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 93.1 10.33 1 52 0 1
#> 179.1 18.63 1 42 0 0
#> 130.1 16.47 1 53 0 1
#> 40 18.00 1 28 1 0
#> 154 12.63 1 20 1 0
#> 37.1 12.52 1 57 1 0
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 124 9.73 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 68.2 20.62 1 44 0 0
#> 15.1 22.68 1 48 0 0
#> 179.2 18.63 1 42 0 0
#> 37.2 12.52 1 57 1 0
#> 150.2 20.33 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 183 9.24 1 67 1 0
#> 177.1 12.53 1 75 0 0
#> 113.1 22.86 1 34 0 0
#> 110.1 17.56 1 65 0 1
#> 197 21.60 1 69 1 0
#> 36 21.19 1 48 0 1
#> 150.3 20.33 1 48 0 0
#> 100 16.07 1 60 0 0
#> 161 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 83 24.00 0 6 0 0
#> 74 24.00 0 43 0 1
#> 83.1 24.00 0 6 0 0
#> 163 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 47 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 147.1 24.00 0 76 1 0
#> 185 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 2.1 24.00 0 9 0 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 102 24.00 0 49 0 0
#> 102.1 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 121.1 24.00 0 57 1 0
#> 35.1 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 161.1 24.00 0 45 0 0
#> 48 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 191 24.00 0 60 0 1
#> 112 24.00 0 61 0 0
#> 163.1 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 54.1 24.00 0 53 1 0
#> 73 24.00 0 NA 0 1
#> 46 24.00 0 71 0 0
#> 71.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 28.1 24.00 0 67 1 0
#> 143 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 80.1 24.00 0 41 0 0
#> 62.1 24.00 0 71 0 0
#> 72.1 24.00 0 40 0 1
#> 71.2 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 142 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 38 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 74.1 24.00 0 43 0 1
#> 54.2 24.00 0 53 1 0
#> 72.2 24.00 0 40 0 1
#> 22.1 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 67.1 24.00 0 25 0 0
#> 135.1 24.00 0 58 1 0
#> 119.3 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 64.1 24.00 0 43 0 0
#> 121.2 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 35.2 24.00 0 51 0 0
#> 71.3 24.00 0 51 0 0
#> 71.4 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 185.1 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 198.1 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 182.1 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.499 NA NA NA
#> 2 age, Cure model 0.0118 NA NA NA
#> 3 grade_ii, Cure model -0.0592 NA NA NA
#> 4 grade_iii, Cure model 0.572 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00283 NA NA NA
#> 2 grade_ii, Survival model 0.697 NA NA NA
#> 3 grade_iii, Survival model 0.696 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49937 0.01179 -0.05924 0.57152
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49937080 0.01178743 -0.05923753 0.57152132
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002830105 0.696791349 0.695823982
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.05959435 0.30054095 0.97229915 0.47270117 0.77766841 0.26852421
#> [7] 0.10670084 0.68874192 0.49251887 0.43350263 0.52109819 0.68874192
#> [13] 0.78560827 0.52109819 0.18318559 0.24569819 0.61210474 0.76181497
#> [19] 0.42343828 0.92937200 0.99306311 0.56724925 0.96520232 0.04104357
#> [25] 0.01347848 0.73811406 0.63800219 0.57637283 0.92204311 0.76973661
#> [31] 0.40320622 0.13481047 0.34203286 0.68038770 0.53976931 0.92937200
#> [37] 0.51171211 0.07929144 0.59455502 0.55801861 0.13481047 0.87014246
#> [43] 0.87773883 0.90736575 0.34203286 0.68874192 0.39281619 0.44341320
#> [49] 0.40320622 0.65504447 0.73811406 0.89990862 0.84758222 0.80893235
#> [55] 0.63800219 0.83218296 0.66354135 0.71359526 0.30054095 0.24569819
#> [61] 0.97229915 0.95099225 0.61210474 0.61210474 0.97229915 0.95099225
#> [67] 0.72995394 0.01347848 0.71359526 0.28993984 0.87773883 0.15876088
#> [73] 0.73811406 0.20801889 0.81670143 0.79348235 0.48269095 0.18318559
#> [79] 0.79348235 0.87773883 0.33160965 0.90736575 0.44341320 0.59455502
#> [85] 0.50219382 0.82447478 0.84758222 0.38246097 0.58551937 0.07929144
#> [91] 0.30054095 0.15876088 0.44341320 0.84758222 0.34203286 0.20801889
#> [97] 0.94379132 0.83218296 0.10670084 0.53976931 0.23319984 0.26852421
#> [103] 0.34203286 0.67195628 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 168 68 25 8 180 99 113 6 41 97 184 6.1 96
#> 23.72 20.62 6.32 18.43 14.82 21.19 22.86 15.64 18.02 19.14 17.77 15.64 14.54
#> 184.1 169 139 85 18 76 187 127 45 77 78 24 29
#> 17.77 22.41 21.49 16.44 15.21 19.22 9.92 3.53 17.42 7.27 23.88 23.89 15.45
#> 5 23 145 157 55 63 150 26 110 187.1 134 164 130
#> 16.43 16.92 10.07 15.10 19.34 22.77 20.33 15.77 17.56 9.92 17.81 23.60 16.47
#> 30 63.1 56 159 93 150.1 6.2 166 179 58 79 29.1 10
#> 17.43 22.77 12.21 10.55 10.33 20.33 15.64 19.98 18.63 19.34 16.23 15.45 10.53
#> 37 81 5.1 177 188 39 68.1 139.1 25.1 16 85.1 192 25.2
#> 12.52 14.06 16.43 12.53 16.16 15.59 20.62 21.49 6.32 8.71 16.44 16.44 6.32
#> 16.1 167 24.1 39.1 190 159.1 15 29.2 175 14 13 108 169.1
#> 8.71 15.55 23.89 15.59 20.81 10.55 22.68 15.45 21.91 12.89 14.34 18.29 22.41
#> 13.1 159.2 128 93.1 179.1 130.1 40 154 37.1 158 171 164.1 68.2
#> 14.34 10.55 20.35 10.33 18.63 16.47 18.00 12.63 12.52 20.14 16.57 23.60 20.62
#> 15.1 179.2 37.2 150.2 175.1 183 177.1 113.1 110.1 197 36 150.3 100
#> 22.68 18.63 12.52 20.33 21.91 9.24 12.53 22.86 17.56 21.60 21.19 20.33 16.07
#> 161 21 67 144 54 83 74 83.1 163 2 147 47 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 185 64 2.1 71 22 121 35 80 182 102 102.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 35.1 200 165 198 119 118 144.1 161.1 48 191 112 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 120 146 31 132 152 54.1 46 71.1 62 9 119.1 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 72 80.1 62.1 72.1 71.2 119.2 142 135 38 44 74.1 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.2 22.1 20 67.1 135.1 119.3 11 64.1 121.2 176 35.2 71.3 71.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 185.1 17 174 198.1 186 182.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01077708 0.90816086 0.47117527
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.523737448 -0.002025156 -0.727586571
#> grade_iii, Cure model
#> 0.137859947
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 45 17.42 1 54 0 1
#> 93 10.33 1 52 0 1
#> 101 9.97 1 10 0 1
#> 68 20.62 1 44 0 0
#> 92 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 179 18.63 1 42 0 0
#> 6 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 133 14.65 1 57 0 0
#> 30 17.43 1 78 0 0
#> 136 21.83 1 43 0 1
#> 159 10.55 1 50 0 1
#> 107 11.18 1 54 1 0
#> 25 6.32 1 34 1 0
#> 25.1 6.32 1 34 1 0
#> 136.1 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 91 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 150.1 20.33 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 155 13.08 1 26 0 0
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 76.1 19.22 1 54 0 1
#> 56 12.21 1 60 0 0
#> 150.2 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 149 8.37 1 33 1 0
#> 45.1 17.42 1 54 0 1
#> 10 10.53 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 139 21.49 1 63 1 0
#> 124.1 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 139.1 21.49 1 63 1 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 77 7.27 1 67 0 1
#> 15 22.68 1 48 0 0
#> 139.2 21.49 1 63 1 0
#> 8 18.43 1 32 0 0
#> 8.1 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 55 19.34 1 69 0 1
#> 150.3 20.33 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 168 23.72 1 70 0 0
#> 69.1 23.23 1 25 0 1
#> 30.1 17.43 1 78 0 0
#> 150.4 20.33 1 48 0 0
#> 23 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 49 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 40.1 18.00 1 28 1 0
#> 164 23.60 1 76 0 1
#> 150.5 20.33 1 48 0 0
#> 90 20.94 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 88.1 18.37 1 47 0 0
#> 8.2 18.43 1 32 0 0
#> 40.2 18.00 1 28 1 0
#> 52 10.42 1 52 0 1
#> 145 10.07 1 65 1 0
#> 70 7.38 1 30 1 0
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 130 16.47 1 53 0 1
#> 29 15.45 1 68 1 0
#> 25.2 6.32 1 34 1 0
#> 169.1 22.41 1 46 0 0
#> 76.2 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 40.3 18.00 1 28 1 0
#> 180.1 14.82 1 37 0 0
#> 168.1 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 154 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 150.6 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 188 16.16 1 46 0 1
#> 93.1 10.33 1 52 0 1
#> 41 18.02 1 40 1 0
#> 37 12.52 1 57 1 0
#> 101.2 9.97 1 10 0 1
#> 89.1 11.44 1 NA 0 0
#> 29.1 15.45 1 68 1 0
#> 96 14.54 1 33 0 1
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 40.4 18.00 1 28 1 0
#> 6.1 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 68.2 20.62 1 44 0 0
#> 43.1 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 108.1 18.29 1 39 0 1
#> 171 16.57 1 41 0 1
#> 175 21.91 1 43 0 0
#> 121 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 116 24.00 0 58 0 1
#> 54 24.00 0 53 1 0
#> 198.1 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 116.1 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 160 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 9.1 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 138.1 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 173 24.00 0 19 0 1
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 185.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 34.1 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 104 24.00 0 50 1 0
#> 47.1 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 178 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 87 24.00 0 27 0 0
#> 137.2 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 160.2 24.00 0 31 1 0
#> 160.3 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 9.2 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 47.2 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 74 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 87.1 24.00 0 27 0 0
#> 135 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 163.1 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 103.2 24.00 0 56 1 0
#> 74.1 24.00 0 43 0 1
#> 34.2 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 186.2 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 121.1 24.00 0 57 1 0
#> 172.1 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 152 24.00 0 36 0 1
#> 143.1 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 191.1 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 115.1 24.00 0 NA 1 0
#> 165 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.524 NA NA NA
#> 2 age, Cure model -0.00203 NA NA NA
#> 3 grade_ii, Cure model -0.728 NA NA NA
#> 4 grade_iii, Cure model 0.138 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0108 NA NA NA
#> 2 grade_ii, Survival model 0.908 NA NA NA
#> 3 grade_iii, Survival model 0.471 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.523737 -0.002025 -0.727587 0.137860
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 254.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.523737448 -0.002025156 -0.727586571 0.137859947
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01077708 0.90816086 0.47117527
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6389131517 0.4784917635 0.8421485141 0.8826834777 0.1446163593
#> [6] 0.0338516634 0.3460927332 0.2929105244 0.5989814027 0.5889980450
#> [11] 0.5589672342 0.1701544278 0.5789799609 0.6692430543 0.4586824382
#> [16] 0.0949720788 0.8117391392 0.8016399569 0.9519714546 0.9519714546
#> [21] 0.0949720788 0.4016492197 0.9806453879 0.4489110968 0.1701544278
#> [26] 0.5390012692 0.7103045201 0.2523800207 0.8826834777 0.2523800207
#> [31] 0.7611966328 0.1701544278 0.0008150852 0.9223193019 0.4784917635
#> [36] 0.8218465521 0.1123961853 0.0539719909 0.1123961853 0.0221652764
#> [41] 0.5390012692 0.9420999324 0.0403579760 0.1123961853 0.3140271440
#> [46] 0.3140271440 0.2318658701 0.0403579760 0.2420710978 0.1701544278
#> [51] 0.2929105244 0.0039949434 0.0221652764 0.4586824382 0.1701544278
#> [56] 0.4983875742 0.7000829327 0.7713658982 0.1446163593 0.4016492197
#> [61] 0.0142840123 0.1701544278 0.1361521106 0.6692430543 0.3460927332
#> [66] 0.3140271440 0.4016492197 0.8319922460 0.8725453641 0.9322513093
#> [71] 0.9123077739 0.6490069764 0.5186771742 0.6190089463 0.9519714546
#> [76] 0.0539719909 0.2523800207 0.0690904948 0.4016492197 0.6490069764
#> [81] 0.0039949434 0.9903142388 0.7308495054 0.5288378812 0.1701544278
#> [86] 0.7814714506 0.5689714597 0.8421485141 0.3905780236 0.7409941898
#> [91] 0.8826834777 0.6190089463 0.6897639514 0.3683702067 0.8623799940
#> [96] 0.4016492197 0.5989814027 0.0690904948 0.7205621814 0.7510916533
#> [101] 0.1446163593 0.7814714506 0.2824351113 0.3683702067 0.5085353810
#> [106] 0.0858102286 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 157 45 93 101 68 92 88 179 6 125 79 150 26
#> 15.10 17.42 10.33 9.97 20.62 22.92 18.37 18.63 15.64 15.65 16.23 20.33 15.77
#> 133 30 136 159 107 25 25.1 136.1 40 91 134 150.1 192
#> 14.65 17.43 21.83 10.55 11.18 6.32 6.32 21.83 18.00 5.33 17.81 20.33 16.44
#> 155 76 101.1 76.1 56 150.2 78 149 45.1 10 139 169 139.1
#> 13.08 19.22 9.97 19.22 12.21 20.33 23.88 8.37 17.42 10.53 21.49 22.41 21.49
#> 69 85 77 15 139.2 8 8.1 166 15.1 55 150.3 179.1 168
#> 23.23 16.44 7.27 22.68 21.49 18.43 18.43 19.98 22.68 19.34 20.33 18.63 23.72
#> 69.1 30.1 150.4 23 60 49 68.1 40.1 164 150.5 90 133.1 88.1
#> 23.23 17.43 20.33 16.92 13.15 12.19 20.62 18.00 23.60 20.33 20.94 14.65 18.37
#> 8.2 40.2 52 145 70 16 180 130 29 25.2 169.1 76.2 66
#> 18.43 18.00 10.42 10.07 7.38 8.71 14.82 16.47 15.45 6.32 22.41 19.22 22.13
#> 40.3 180.1 168.1 127 154 181 150.6 43 188 93.1 41 37 101.2
#> 18.00 14.82 23.72 3.53 12.63 16.46 20.33 12.10 16.16 10.33 18.02 12.52 9.97
#> 29.1 96 108 61 40.4 6.1 66.1 14 42 68.2 43.1 97 108.1
#> 15.45 14.54 18.29 10.12 18.00 15.64 22.13 12.89 12.43 20.62 12.10 19.14 18.29
#> 171 175 121 198 116 54 198.1 62 2 156 138 17 126
#> 16.57 21.91 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 28 116.1 12 174 9 137 160 119 9.1 172 138.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 185 72 185.1 34 137.1 31 19 34.1 47 103 104 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 163 28.1 178 54.1 102 87 137.2 151 162 160.2 160.3 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 103.1 47.2 27 74 12.1 87.1 135 102.1 163.1 186 27.1 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.2 74.1 34.2 71 191 186.2 112 121.1 172.1 143 144 152 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 38 161 191.1 193 165 71.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01094796 0.59246239 0.19101108
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.64498772 0.01340088 0.27576422
#> grade_iii, Cure model
#> 0.47714150
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 101 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 60 13.15 1 38 1 0
#> 68 20.62 1 44 0 0
#> 92 22.92 1 47 0 1
#> 49 12.19 1 48 1 0
#> 92.1 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 154.1 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 45 17.42 1 54 0 1
#> 183 9.24 1 67 1 0
#> 170 19.54 1 43 0 1
#> 197 21.60 1 69 1 0
#> 159 10.55 1 50 0 1
#> 195 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 51 18.23 1 83 0 1
#> 133 14.65 1 57 0 0
#> 90 20.94 1 50 0 1
#> 101.1 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 129 23.41 1 53 1 0
#> 153.1 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 92.2 22.92 1 47 0 1
#> 29 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 56 12.21 1 60 0 0
#> 85 16.44 1 36 0 0
#> 70 7.38 1 30 1 0
#> 139.1 21.49 1 63 1 0
#> 39 15.59 1 37 0 1
#> 166 19.98 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 68.1 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 91 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 63 22.77 1 31 1 0
#> 157 15.10 1 47 0 0
#> 123 13.00 1 44 1 0
#> 70.1 7.38 1 30 1 0
#> 14 12.89 1 21 0 0
#> 99 21.19 1 38 0 1
#> 168 23.72 1 70 0 0
#> 111 17.45 1 47 0 1
#> 32 20.90 1 37 1 0
#> 107 11.18 1 54 1 0
#> 133.1 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 85.1 16.44 1 36 0 0
#> 197.1 21.60 1 69 1 0
#> 60.1 13.15 1 38 1 0
#> 51.1 18.23 1 83 0 1
#> 37 12.52 1 57 1 0
#> 24 23.89 1 38 0 0
#> 100 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 149.1 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 69 23.23 1 25 0 1
#> 170.1 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 60.2 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 113 22.86 1 34 0 0
#> 166.1 19.98 1 48 0 0
#> 96 14.54 1 33 0 1
#> 189 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 184.1 17.77 1 38 0 0
#> 197.2 21.60 1 69 1 0
#> 190 20.81 1 42 1 0
#> 133.2 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 194 22.40 1 38 0 1
#> 145.1 10.07 1 65 1 0
#> 108 18.29 1 39 0 1
#> 136 21.83 1 43 0 1
#> 117 17.46 1 26 0 1
#> 117.1 17.46 1 26 0 1
#> 10.1 10.53 1 34 0 0
#> 153.2 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 51.2 18.23 1 83 0 1
#> 88.1 18.37 1 47 0 0
#> 85.2 16.44 1 36 0 0
#> 13 14.34 1 54 0 1
#> 16 8.71 1 71 0 1
#> 167.1 15.55 1 56 1 0
#> 60.3 13.15 1 38 1 0
#> 168.1 23.72 1 70 0 0
#> 123.1 13.00 1 44 1 0
#> 134 17.81 1 47 1 0
#> 154.2 12.63 1 20 1 0
#> 145.2 10.07 1 65 1 0
#> 169.1 22.41 1 46 0 0
#> 170.2 19.54 1 43 0 1
#> 179 18.63 1 42 0 0
#> 60.4 13.15 1 38 1 0
#> 130 16.47 1 53 0 1
#> 195.1 11.76 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 125 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 126 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 94 24.00 0 51 0 1
#> 137.1 24.00 0 45 1 0
#> 21 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#> 126.1 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 9 24.00 0 31 1 0
#> 137.2 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 122 24.00 0 66 0 0
#> 126.2 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 193.1 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 174 24.00 0 49 1 0
#> 156 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 144.1 24.00 0 28 0 1
#> 47 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 112.1 24.00 0 61 0 0
#> 193.2 24.00 0 45 0 1
#> 2.1 24.00 0 9 0 0
#> 138.1 24.00 0 44 1 0
#> 2.2 24.00 0 9 0 0
#> 2.3 24.00 0 9 0 0
#> 19 24.00 0 57 0 1
#> 7.1 24.00 0 37 1 0
#> 156.1 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 35.1 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 7.2 24.00 0 37 1 0
#> 141 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 47.1 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 144.2 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 2.4 24.00 0 9 0 0
#> 75.1 24.00 0 21 1 0
#> 152 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 182.1 24.00 0 35 0 0
#> 20.1 24.00 0 46 1 0
#> 141.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 137.3 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 35.2 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 156.2 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 185.1 24.00 0 44 1 0
#> 3.2 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 46.1 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.645 NA NA NA
#> 2 age, Cure model 0.0134 NA NA NA
#> 3 grade_ii, Cure model 0.276 NA NA NA
#> 4 grade_iii, Cure model 0.477 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0109 NA NA NA
#> 2 grade_ii, Survival model 0.592 NA NA NA
#> 3 grade_iii, Survival model 0.191 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.6450 0.0134 0.2758 0.4771
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 269.7
#> Residual Deviance: 266 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64498772 0.01340088 0.27576422 0.47714150
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01094796 0.59246239 0.19101108
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8777023170 0.1271403087 0.6065301988 0.1880483079 0.0218728676
#> [6] 0.7784742563 0.0218728676 0.7033647961 0.9888053145 0.7033647961
#> [11] 0.1121549140 0.3849543713 0.8998724512 0.2287770642 0.0907049836
#> [16] 0.8114172184 0.0557207685 0.2987897583 0.5405538405 0.1567388080
#> [21] 0.8777023170 0.0758634707 0.0112110996 0.1271403087 0.7894167545
#> [26] 0.0218728676 0.5191262245 0.4351264432 0.7567220521 0.4049856305
#> [31] 0.9555893356 0.1121549140 0.4874307443 0.2121311354 0.8998724512
#> [36] 0.1880483079 0.2716311002 0.9776593387 0.3363981603 0.0433334760
#> [41] 0.5297964571 0.6596806429 0.9555893356 0.6813940549 0.1489877162
#> [46] 0.0031845378 0.3750642200 0.1723087806 0.8004170815 0.5405538405
#> [51] 0.9333642632 0.5953105441 0.1567388080 0.8445874575 0.4049856305
#> [56] 0.0907049836 0.6065301988 0.2987897583 0.7351580983 0.0006993437
#> [61] 0.4558533852 0.4454900623 0.9333642632 0.2039076081 0.0164663305
#> [66] 0.2287770642 0.2539461065 0.6065301988 0.4768405230 0.0370487026
#> [71] 0.2121311354 0.5730717278 0.4980654985 0.3363981603 0.0907049836
#> [76] 0.1802028884 0.5405538405 0.8224622470 0.0688237551 0.8445874575
#> [81] 0.2896003579 0.0832033163 0.3556841076 0.3556841076 0.8224622470
#> [86] 0.1271403087 0.7459173132 0.0493681199 0.2987897583 0.2716311002
#> [91] 0.4049856305 0.5841562318 0.9221146993 0.4980654985 0.6065301988
#> [96] 0.0031845378 0.6596806429 0.3268029875 0.7033647961 0.8445874575
#> [101] 0.0557207685 0.2287770642 0.2627337489 0.6065301988 0.3949290490
#> [106] 0.7567220521 0.4663314177 0.6923748865 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [196] 0.0000000000
#>
#> $Time
#> 101 153 60 68 92 49 92.1 154 127 154.1 139 45 183
#> 9.97 21.33 13.15 20.62 22.92 12.19 22.92 12.63 3.53 12.63 21.49 17.42 9.24
#> 170 197 159 169 51 133 90 101.1 66 129 153.1 43 92.2
#> 19.54 21.60 10.55 22.41 18.23 14.65 20.94 9.97 22.13 23.41 21.33 12.10 22.92
#> 29 5 56 85 70 139.1 39 166 183.1 68.1 88 91 184
#> 15.45 16.43 12.21 16.44 7.38 21.49 15.59 19.98 9.24 20.62 18.37 5.33 17.77
#> 63 157 123 70.1 14 99 168 111 32 107 133.1 149 81
#> 22.77 15.10 13.00 7.38 12.89 21.19 23.72 17.45 20.90 11.18 14.65 8.37 14.06
#> 90.1 145 85.1 197.1 60.1 51.1 37 24 100 79 149.1 150 69
#> 20.94 10.07 16.44 21.60 13.15 18.23 12.52 23.89 16.07 16.23 8.37 20.33 23.23
#> 170.1 58 60.2 6 113 166.1 96 167 184.1 197.2 190 133.2 10
#> 19.54 19.34 13.15 15.64 22.86 19.98 14.54 15.55 17.77 21.60 20.81 14.65 10.53
#> 194 145.1 108 136 117 117.1 10.1 153.2 42 15 51.2 88.1 85.2
#> 22.40 10.07 18.29 21.83 17.46 17.46 10.53 21.33 12.43 22.68 18.23 18.37 16.44
#> 13 16 167.1 60.3 168.1 123.1 134 154.2 145.2 169.1 170.2 179 60.4
#> 14.34 8.71 15.55 13.15 23.72 13.00 17.81 12.63 10.07 22.41 19.54 18.63 13.15
#> 130 56.1 125 140 126 131 173 137 121 17 112 2 94
#> 16.47 12.21 15.65 12.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 21 94.1 126.1 138 95 102 35 82 44 9 137.2 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 126.2 144 34 120 193.1 161 174 156 95.1 7 144.1 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 112.1 193.2 2.1 138.1 2.2 2.3 19 7.1 156.1 118 20 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 35.1 132 7.2 141 75 47.1 48 3 161.1 144.2 62 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 109 185 2.4 75.1 152 3.1 62.1 182 182.1 20.1 141.1 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.3 33 198 35.2 162 156.2 176 65 185.1 3.2 21.1 121.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01084999 0.50155037 0.24287369
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.088206716 -0.004936251 0.443104545
#> grade_iii, Cure model
#> 1.304927818
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 57 14.46 1 45 0 1
#> 81 14.06 1 34 0 0
#> 166 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 183 9.24 1 67 1 0
#> 66 22.13 1 53 0 0
#> 63 22.77 1 31 1 0
#> 149 8.37 1 33 1 0
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 190 20.81 1 42 1 0
#> 97 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 92 22.92 1 47 0 1
#> 155.1 13.08 1 26 0 0
#> 101 9.97 1 10 0 1
#> 41 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 60 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 114 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 92.1 22.92 1 47 0 1
#> 68.1 20.62 1 44 0 0
#> 29 15.45 1 68 1 0
#> 188.1 16.16 1 46 0 1
#> 194 22.40 1 38 0 1
#> 101.1 9.97 1 10 0 1
#> 158 20.14 1 74 1 0
#> 167 15.55 1 56 1 0
#> 25.1 6.32 1 34 1 0
#> 36 21.19 1 48 0 1
#> 157 15.10 1 47 0 0
#> 128 20.35 1 35 0 1
#> 134 17.81 1 47 1 0
#> 63.1 22.77 1 31 1 0
#> 111 17.45 1 47 0 1
#> 167.1 15.55 1 56 1 0
#> 97.1 19.14 1 65 0 1
#> 76.1 19.22 1 54 0 1
#> 10 10.53 1 34 0 0
#> 183.1 9.24 1 67 1 0
#> 68.2 20.62 1 44 0 0
#> 192 16.44 1 31 1 0
#> 97.2 19.14 1 65 0 1
#> 139.1 21.49 1 63 1 0
#> 14 12.89 1 21 0 0
#> 92.2 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 15 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 190.1 20.81 1 42 1 0
#> 139.2 21.49 1 63 1 0
#> 114.1 13.68 1 NA 0 0
#> 45.1 17.42 1 54 0 1
#> 175 21.91 1 43 0 0
#> 114.2 13.68 1 NA 0 0
#> 10.1 10.53 1 34 0 0
#> 86 23.81 1 58 0 1
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 79 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 140 12.68 1 59 1 0
#> 123.1 13.00 1 44 1 0
#> 159.1 10.55 1 50 0 1
#> 40 18.00 1 28 1 0
#> 41.1 18.02 1 40 1 0
#> 101.2 9.97 1 10 0 1
#> 88 18.37 1 47 0 0
#> 180 14.82 1 37 0 0
#> 15.1 22.68 1 48 0 0
#> 97.3 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 89 11.44 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 167.2 15.55 1 56 1 0
#> 149.1 8.37 1 33 1 0
#> 123.2 13.00 1 44 1 0
#> 97.4 19.14 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 78.1 23.88 1 43 0 0
#> 15.2 22.68 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 124.1 9.73 1 NA 1 0
#> 68.3 20.62 1 44 0 0
#> 133.1 14.65 1 57 0 0
#> 130 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 58 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 175.1 21.91 1 43 0 0
#> 81.1 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 105 19.75 1 60 0 0
#> 18 15.21 1 49 1 0
#> 51 18.23 1 83 0 1
#> 114.3 13.68 1 NA 0 0
#> 183.2 9.24 1 67 1 0
#> 179 18.63 1 42 0 0
#> 136.1 21.83 1 43 0 1
#> 101.3 9.97 1 10 0 1
#> 191 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 165 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 35 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 200 24.00 0 64 0 0
#> 137 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 137.1 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 148 24.00 0 61 1 0
#> 104 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 165.2 24.00 0 47 0 0
#> 131.1 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 200.1 24.00 0 64 0 0
#> 3.1 24.00 0 31 1 0
#> 200.2 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 21 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 3.2 24.00 0 31 1 0
#> 132.2 24.00 0 55 0 0
#> 186.1 24.00 0 45 1 0
#> 54.1 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 98 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 131.2 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 17 24.00 0 38 0 1
#> 71.2 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 198.2 24.00 0 66 0 1
#> 44 24.00 0 56 0 0
#> 185.1 24.00 0 44 1 0
#> 132.3 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 22 24.00 0 52 1 0
#> 73 24.00 0 NA 0 1
#> 11.1 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 165.3 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 9.1 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0882 NA NA NA
#> 2 age, Cure model -0.00494 NA NA NA
#> 3 grade_ii, Cure model 0.443 NA NA NA
#> 4 grade_iii, Cure model 1.30 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0108 NA NA NA
#> 2 grade_ii, Survival model 0.502 NA NA NA
#> 3 grade_iii, Survival model 0.243 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.088207 -0.004936 0.443105 1.304928
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 249.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.088206716 -0.004936251 0.443104545 1.304927818
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01084999 0.50155037 0.24287369
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.651567697 0.662988484 0.237607120 0.018202507 0.870768622 0.085914909
#> [7] 0.047931154 0.905777029 0.123445794 0.697396544 0.964437427 0.351404399
#> [13] 0.777955140 0.162762280 0.283846887 0.265165409 0.498232018 0.434293159
#> [19] 0.030611783 0.697396544 0.824777135 0.372159564 0.466020887 0.720435842
#> [25] 0.685874531 0.929175349 0.941006633 0.178743470 0.030611783 0.178743470
#> [31] 0.584602954 0.498232018 0.078863122 0.824777135 0.220135782 0.552229356
#> [37] 0.941006633 0.154527038 0.606689956 0.211403927 0.403026673 0.047931154
#> [43] 0.423801238 0.552229356 0.283846887 0.265165409 0.801260611 0.870768622
#> [49] 0.178743470 0.476780518 0.283846887 0.123445794 0.754677488 0.030611783
#> [55] 0.024380818 0.059785317 0.988064715 0.413369857 0.162762280 0.123445794
#> [61] 0.434293159 0.093229447 0.801260611 0.007266532 0.629011582 0.001475204
#> [67] 0.487496719 0.530559849 0.766304873 0.720435842 0.777955140 0.392685723
#> [73] 0.372159564 0.824777135 0.341148200 0.617817435 0.059785317 0.283846887
#> [79] 0.220135782 0.012187297 0.552229356 0.905777029 0.720435842 0.283846887
#> [85] 0.964437427 0.001475204 0.059785317 0.530559849 0.178743470 0.629011582
#> [91] 0.455315049 0.108124728 0.255848431 0.146397006 0.093229447 0.662988484
#> [97] 0.519678060 0.246647084 0.595643417 0.361710233 0.870768622 0.331013727
#> [103] 0.108124728 0.824777135 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 57 81 166 129 183 66 63 149 139 155 91 108 159
#> 14.46 14.06 19.98 23.41 9.24 22.13 22.77 8.37 21.49 13.08 5.33 18.29 10.55
#> 190 97 76 188 45 92 155.1 101 41 181 123 60 77
#> 20.81 19.14 19.22 16.16 17.42 22.92 13.08 9.97 18.02 16.46 13.00 13.15 7.27
#> 25 68 92.1 68.1 29 188.1 194 101.1 158 167 25.1 36 157
#> 6.32 20.62 22.92 20.62 15.45 16.16 22.40 9.97 20.14 15.55 6.32 21.19 15.10
#> 128 134 63.1 111 167.1 97.1 76.1 10 183.1 68.2 192 97.2 139.1
#> 20.35 17.81 22.77 17.45 15.55 19.14 19.22 10.53 9.24 20.62 16.44 19.14 21.49
#> 14 92.2 69 15 127 184 190.1 139.2 45.1 175 10.1 86 133
#> 12.89 22.92 23.23 22.68 3.53 17.77 20.81 21.49 17.42 21.91 10.53 23.81 14.65
#> 78 79 39 140 123.1 159.1 40 41.1 101.2 88 180 15.1 97.3
#> 23.88 16.23 15.59 12.68 13.00 10.55 18.00 18.02 9.97 18.37 14.82 22.68 19.14
#> 158.1 164 167.2 149.1 123.2 97.4 91.1 78.1 15.2 39.1 68.3 133.1 130
#> 20.14 23.60 15.55 8.37 13.00 19.14 5.33 23.88 22.68 15.59 20.62 14.65 16.47
#> 136 58 153 175.1 81.1 125 105 18 51 183.2 179 136.1 101.3
#> 21.83 19.34 21.33 21.91 14.06 15.65 19.75 15.21 18.23 9.24 18.63 21.83 9.97
#> 191 165 74 165.1 141 118 131 48 33 71 48.1 62 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 35 11 200 137 28 172 35.1 74.1 152 137.1 102 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 3 71.1 142 9 163 186 165.2 131.1 28.1 176 185 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 3.1 200.2 87 46 198 54 21 67 103 156 198.1 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 132.2 186.1 54.1 20 20.1 143 151 98 193 131.2 98.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 152.1 47 198.2 44 185.1 132.3 174 178 196 22 11.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 165.3 38 161 80 9.1 33.1 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01928097 0.49745030 0.43254684
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.311509647 -0.007322429 -0.685791274
#> grade_iii, Cure model
#> 1.004283888
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 96 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 130 16.47 1 53 0 1
#> 36 21.19 1 48 0 1
#> 96.1 14.54 1 33 0 1
#> 42 12.43 1 49 0 1
#> 81 14.06 1 34 0 0
#> 180 14.82 1 37 0 0
#> 13 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 15.1 22.68 1 48 0 0
#> 194 22.40 1 38 0 1
#> 96.2 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 78 23.88 1 43 0 0
#> 125 15.65 1 67 1 0
#> 92.1 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 90 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 58 19.34 1 39 0 0
#> 194.1 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 85 16.44 1 36 0 0
#> 15.2 22.68 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 10 10.53 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 76 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 92.2 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 16 8.71 1 71 0 1
#> 92.3 22.92 1 47 0 1
#> 55.1 19.34 1 69 0 1
#> 159 10.55 1 50 0 1
#> 158 20.14 1 74 1 0
#> 13.1 14.34 1 54 0 1
#> 14 12.89 1 21 0 0
#> 58.1 19.34 1 39 0 0
#> 139 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 8 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 13.2 14.34 1 54 0 1
#> 55.2 19.34 1 69 0 1
#> 96.3 14.54 1 33 0 1
#> 111 17.45 1 47 0 1
#> 168 23.72 1 70 0 0
#> 58.2 19.34 1 39 0 0
#> 58.3 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 105 19.75 1 60 0 0
#> 93 10.33 1 52 0 1
#> 5 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 199.1 19.81 1 NA 0 1
#> 13.3 14.34 1 54 0 1
#> 179.1 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 8.1 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 113 22.86 1 34 0 0
#> 26 15.77 1 49 0 1
#> 66 22.13 1 53 0 0
#> 92.4 22.92 1 47 0 1
#> 101 9.97 1 10 0 1
#> 42.1 12.43 1 49 0 1
#> 171 16.57 1 41 0 1
#> 167 15.55 1 56 1 0
#> 166.1 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 181 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 4.1 17.64 1 NA 0 1
#> 76.1 19.22 1 54 0 1
#> 124.1 9.73 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 58.4 19.34 1 39 0 0
#> 106.1 16.67 1 49 1 0
#> 184.1 17.77 1 38 0 0
#> 125.1 15.65 1 67 1 0
#> 114.1 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 108 18.29 1 39 0 1
#> 108.1 18.29 1 39 0 1
#> 117 17.46 1 26 0 1
#> 55.3 19.34 1 69 0 1
#> 199.2 19.81 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 13.4 14.34 1 54 0 1
#> 169 22.41 1 46 0 0
#> 129 23.41 1 53 1 0
#> 51.1 18.23 1 83 0 1
#> 139.1 21.49 1 63 1 0
#> 39 15.59 1 37 0 1
#> 188.1 16.16 1 46 0 1
#> 92.5 22.92 1 47 0 1
#> 52.1 10.42 1 52 0 1
#> 105.1 19.75 1 60 0 0
#> 37 12.52 1 57 1 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 1.1 24.00 0 23 1 0
#> 64 24.00 0 43 0 0
#> 103 24.00 0 56 1 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 44 24.00 0 56 0 0
#> 34 24.00 0 36 0 0
#> 103.1 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#> 122.1 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 151 24.00 0 42 0 0
#> 138.1 24.00 0 44 1 0
#> 103.2 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 172.1 24.00 0 41 0 0
#> 122.2 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 22.1 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 173 24.00 0 19 0 1
#> 200 24.00 0 64 0 0
#> 67 24.00 0 25 0 0
#> 98.1 24.00 0 34 1 0
#> 64.1 24.00 0 43 0 0
#> 131 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 22.2 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 200.2 24.00 0 64 0 0
#> 20 24.00 0 46 1 0
#> 17 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 48.1 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 95.1 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 148.1 24.00 0 61 1 0
#> 198.1 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 161 24.00 0 45 0 0
#> 22.3 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 135.1 24.00 0 58 1 0
#> 161.1 24.00 0 45 0 0
#> 9 24.00 0 31 1 0
#> 163.2 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 72 24.00 0 40 0 1
#> 137 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 131.1 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 174.1 24.00 0 49 1 0
#> 193.1 24.00 0 45 0 1
#> 84 24.00 0 39 0 1
#> 46 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 44.1 24.00 0 56 0 0
#> 71 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 103.3 24.00 0 56 1 0
#> 176 24.00 0 43 0 1
#> 31.1 24.00 0 36 0 1
#> 80 24.00 0 41 0 0
#> 102.1 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.312 NA NA NA
#> 2 age, Cure model -0.00732 NA NA NA
#> 3 grade_ii, Cure model -0.686 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0193 NA NA NA
#> 2 grade_ii, Survival model 0.497 NA NA NA
#> 3 grade_iii, Survival model 0.433 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.311510 -0.007322 -0.685791 1.004284
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 239.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.311509647 -0.007322429 -0.685791274 1.004283888
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01928097 0.49745030 0.43254684
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.309849e-01 5.876590e-01 7.504817e-01 2.072123e-02 3.751233e-01
#> [6] 5.479506e-02 5.876590e-01 8.146312e-01 7.346772e-01 5.730900e-01
#> [11] 6.597242e-01 6.448138e-01 4.950162e-03 2.072123e-02 3.397007e-02
#> [16] 5.876590e-01 9.653381e-01 2.501702e-05 4.762409e-01 4.950162e-03
#> [21] 9.825888e-01 5.962704e-02 3.997545e-01 1.841848e-01 1.051585e-01
#> [26] 5.030429e-01 1.051585e-01 3.397007e-02 1.931828e-01 3.997545e-01
#> [31] 2.072123e-02 5.030429e-01 8.636758e-01 2.827518e-01 1.670844e-01
#> [36] 6.462617e-02 4.950162e-03 1.788891e-02 9.481271e-01 4.950162e-03
#> [41] 1.051585e-01 8.471336e-01 7.517320e-02 6.597242e-01 7.664185e-01
#> [46] 1.051585e-01 4.585033e-02 6.985678e-02 2.116952e-01 6.597242e-01
#> [51] 1.051585e-01 5.876590e-01 3.278741e-01 2.473415e-04 1.051585e-01
#> [56] 1.051585e-01 4.373584e-01 9.239010e-02 9.139963e-01 4.245920e-01
#> [61] 7.824665e-01 6.597242e-01 1.931828e-01 1.041080e-03 2.116952e-01
#> [66] 8.072740e-02 1.509955e-02 4.630586e-01 4.158683e-02 4.950162e-03
#> [71] 9.311041e-01 8.146312e-01 3.630522e-01 5.446857e-01 8.072740e-02
#> [76] 2.938048e-01 3.873698e-01 3.395428e-01 1.670844e-01 5.446857e-01
#> [81] 1.051585e-01 3.395428e-01 2.938048e-01 4.762409e-01 2.613530e-01
#> [86] 2.410971e-01 2.410971e-01 3.163601e-01 1.051585e-01 8.803719e-01
#> [91] 6.597242e-01 3.015946e-02 2.693995e-03 2.613530e-01 4.585033e-02
#> [96] 5.306216e-01 4.373584e-01 4.950162e-03 8.803719e-01 9.239010e-02
#> [101] 7.984756e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 88 96 155 15 130 36 96.1 42 81 180 13 57 92
#> 18.37 14.54 13.08 22.68 16.47 21.19 14.54 12.43 14.06 14.82 14.34 14.46 22.92
#> 15.1 194 96.2 149 78 125 92.1 91 90 192 97 55 6
#> 22.68 22.40 14.54 8.37 23.88 15.65 22.92 5.33 20.94 16.44 19.14 19.34 15.64
#> 58 194.1 179 85 15.2 6.1 10 134 76 68 92.2 63 16
#> 19.34 22.40 18.63 16.44 22.68 15.64 10.53 17.81 19.22 20.62 22.92 22.77 8.71
#> 92.3 55.1 159 158 13.1 14 58.1 139 128 8 13.2 55.2 96.3
#> 22.92 19.34 10.55 20.14 14.34 12.89 19.34 21.49 20.35 18.43 14.34 19.34 14.54
#> 111 168 58.2 58.3 188 105 93 5 154 13.3 179.1 164 8.1
#> 17.45 23.72 19.34 19.34 16.16 19.75 10.33 16.43 12.63 14.34 18.63 23.60 18.43
#> 166 113 26 66 92.4 101 42.1 171 167 166.1 184 181 106
#> 19.98 22.86 15.77 22.13 22.92 9.97 12.43 16.57 15.55 19.98 17.77 16.46 16.67
#> 76.1 167.1 58.4 106.1 184.1 125.1 51 108 108.1 117 55.3 52 13.4
#> 19.22 15.55 19.34 16.67 17.77 15.65 18.23 18.29 18.29 17.46 19.34 10.42 14.34
#> 169 129 51.1 139.1 39 188.1 92.5 52.1 105.1 37 141 138 1
#> 22.41 23.41 18.23 21.49 15.59 16.16 22.92 10.42 19.75 12.52 24.00 24.00 24.00
#> 172 28 1.1 64 103 142 122 186 102 44 34 103.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 22 151 138.1 103.2 135 98 172.1 122.2 2 22.1 31 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 173 200 67 98.1 64.1 131 200.1 22.2 120 163 200.2 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 160 17.1 148 95 119 48.1 163.1 47 95.1 126 144 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 198.1 156 147 161 22.3 193 94 135.1 161.1 9 163.2 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 137 152 131.1 116 174.1 193.1 84 46 7 44.1 71 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.3 176 31.1 80 102.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003630659 0.631443700 0.315930554
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.204187950 -0.009989028 0.404949393
#> grade_iii, Cure model
#> 1.122338648
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 149 8.37 1 33 1 0
#> 171 16.57 1 41 0 1
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 15 22.68 1 48 0 0
#> 133 14.65 1 57 0 0
#> 18 15.21 1 49 1 0
#> 184 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 117 17.46 1 26 0 1
#> 140 12.68 1 59 1 0
#> 18.1 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 184.1 17.77 1 38 0 0
#> 51 18.23 1 83 0 1
#> 154 12.63 1 20 1 0
#> 68 20.62 1 44 0 0
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 190 20.81 1 42 1 0
#> 92 22.92 1 47 0 1
#> 157 15.10 1 47 0 0
#> 18.2 15.21 1 49 1 0
#> 69 23.23 1 25 0 1
#> 16 8.71 1 71 0 1
#> 68.1 20.62 1 44 0 0
#> 15.1 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 42 12.43 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 66.1 22.13 1 53 0 0
#> 154.1 12.63 1 20 1 0
#> 57.1 14.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 127 3.53 1 62 0 1
#> 55 19.34 1 69 0 1
#> 70.1 7.38 1 30 1 0
#> 184.2 17.77 1 38 0 0
#> 49 12.19 1 48 1 0
#> 37 12.52 1 57 1 0
#> 181 16.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 32 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 139.1 21.49 1 63 1 0
#> 96 14.54 1 33 0 1
#> 76.1 19.22 1 54 0 1
#> 58 19.34 1 39 0 0
#> 78 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 114 13.68 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 32.1 20.90 1 37 1 0
#> 50 10.02 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 6.1 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 69.1 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 194.1 22.40 1 38 0 1
#> 88.1 18.37 1 47 0 0
#> 149.1 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 136 21.83 1 43 0 1
#> 136.1 21.83 1 43 0 1
#> 194.2 22.40 1 38 0 1
#> 107 11.18 1 54 1 0
#> 88.2 18.37 1 47 0 0
#> 42.1 12.43 1 49 0 1
#> 14 12.89 1 21 0 0
#> 49.1 12.19 1 48 1 0
#> 42.2 12.43 1 49 0 1
#> 192.1 16.44 1 31 1 0
#> 101 9.97 1 10 0 1
#> 190.1 20.81 1 42 1 0
#> 42.3 12.43 1 49 0 1
#> 43 12.10 1 61 0 1
#> 4.1 17.64 1 NA 0 1
#> 128.1 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 101.1 9.97 1 10 0 1
#> 100 16.07 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 166 19.98 1 48 0 0
#> 184.3 17.77 1 38 0 0
#> 111 17.45 1 47 0 1
#> 68.2 20.62 1 44 0 0
#> 16.1 8.71 1 71 0 1
#> 194.3 22.40 1 38 0 1
#> 68.3 20.62 1 44 0 0
#> 89.1 11.44 1 NA 0 0
#> 26.2 15.77 1 49 0 1
#> 13.1 14.34 1 54 0 1
#> 49.2 12.19 1 48 1 0
#> 166.1 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 169 22.41 1 46 0 0
#> 171.1 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 133.1 14.65 1 57 0 0
#> 24 23.89 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 126 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 44 24.00 0 56 0 0
#> 1 24.00 0 23 1 0
#> 82 24.00 0 34 0 0
#> 152.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 142.1 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 142.2 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 95 24.00 0 68 0 1
#> 87.1 24.00 0 27 0 0
#> 152.2 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 2 24.00 0 9 0 0
#> 75 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 162.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 44.1 24.00 0 56 0 0
#> 3 24.00 0 31 1 0
#> 152.3 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 104.1 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 44.2 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 176.1 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 44.3 24.00 0 56 0 0
#> 116.1 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 12 24.00 0 63 0 0
#> 109.1 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 80.1 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 109.2 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 112.2 24.00 0 61 0 0
#> 80.2 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 12.1 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 35.1 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 147.2 24.00 0 76 1 0
#> 44.4 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 119.1 24.00 0 17 0 0
#> 185.1 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 103.1 24.00 0 56 1 0
#> 34.1 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.204 NA NA NA
#> 2 age, Cure model -0.00999 NA NA NA
#> 3 grade_ii, Cure model 0.405 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00363 NA NA NA
#> 2 grade_ii, Survival model 0.631 NA NA NA
#> 3 grade_iii, Survival model 0.316 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.204188 -0.009989 0.404949 1.122339
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 255.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.204187950 -0.009989028 0.404949393 1.122338648
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003630659 0.631443700 0.315930554
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.97071895 0.62536816 0.68830652 0.68830652 0.21838440 0.75436001
#> [7] 0.72564647 0.57587036 0.77582237 0.64961732 0.60876389 0.83156830
#> [13] 0.72564647 0.78990190 0.98252648 0.57587036 0.56739163 0.84501135
#> [19] 0.42602470 0.85823935 0.30722335 0.67287350 0.40725029 0.18761928
#> [25] 0.74713902 0.72564647 0.15529261 0.95874840 0.42602470 0.21838440
#> [31] 0.36627773 0.64961732 0.95268549 0.87794603 0.30722335 0.84501135
#> [37] 0.77582237 0.26035957 0.99418041 0.50722193 0.98252648 0.57587036
#> [43] 0.90334572 0.87140384 0.64154185 0.54201471 0.38738647 0.52481103
#> [49] 0.71069162 0.36627773 0.76867019 0.52481103 0.50722193 0.06347129
#> [55] 0.33122103 0.13608159 0.46220817 0.38738647 0.48026670 0.06347129
#> [61] 0.71069162 0.11265538 0.15529261 0.26035957 0.54201471 0.97071895
#> [67] 0.80381562 0.34336975 0.34336975 0.26035957 0.92819714 0.54201471
#> [73] 0.87794603 0.82467054 0.90334572 0.87794603 0.64961732 0.94050815
#> [79] 0.40725029 0.87794603 0.92197507 0.46220817 0.81776820 0.94050815
#> [85] 0.68060065 0.83156830 0.48934965 0.57587036 0.61710102 0.42602470
#> [91] 0.95874840 0.26035957 0.42602470 0.68830652 0.78990190 0.90334572
#> [97] 0.48934965 0.81079488 0.24618992 0.62536816 0.93436595 0.75436001
#> [103] 0.02656139 0.85823935 0.20364174 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 149 171 26 26.1 15 133 18 184 57 85 117 140 18.1
#> 8.37 16.57 15.77 15.77 22.68 14.65 15.21 17.77 14.46 16.44 17.46 12.68 15.21
#> 13 70 184.1 51 154 68 177 66 79 190 92 157 18.2
#> 14.34 7.38 17.77 18.23 12.63 20.62 12.53 22.13 16.23 20.81 22.92 15.10 15.21
#> 69 16 68.1 15.1 139 192 187 42 66.1 154.1 57.1 194 127
#> 23.23 8.71 20.62 22.68 21.49 16.44 9.92 12.43 22.13 12.63 14.46 22.40 3.53
#> 55 70.1 184.2 49 37 181 88 32 76 6 139.1 96 76.1
#> 19.34 7.38 17.77 12.19 12.52 16.46 18.37 20.90 19.22 15.64 21.49 14.54 19.22
#> 58 78 175 129 128 32.1 150 78.1 6.1 164 69.1 194.1 88.1
#> 19.34 23.88 21.91 23.41 20.35 20.90 20.33 23.88 15.64 23.60 23.23 22.40 18.37
#> 149.1 81 136 136.1 194.2 107 88.2 42.1 14 49.1 42.2 192.1 101
#> 8.37 14.06 21.83 21.83 22.40 11.18 18.37 12.43 12.89 12.19 12.43 16.44 9.97
#> 190.1 42.3 43 128.1 123 101.1 100 140.1 166 184.3 111 68.2 16.1
#> 20.81 12.43 12.10 20.35 13.00 9.97 16.07 12.68 19.98 17.77 17.45 20.62 8.71
#> 194.3 68.3 26.2 13.1 49.2 166.1 155 169 171.1 93 133.1 24 177.1
#> 22.40 20.62 15.77 14.34 12.19 19.98 13.08 22.41 16.57 10.33 14.65 23.89 12.53
#> 63 126 87 116 152 148 44 1 82 152.1 104 142 151
#> 22.77 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 109 64 9 46 142.2 20 95 87.1 152.2 132 112 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 137 131 2.1 176 162 141 112.1 22 162.1 121 35 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 103 44.1 3 152.3 196.1 104.1 178 44.2 74 176.1 71 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 17 119 44.3 116.1 185 72 12 109.1 9.1 17.1 34 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 147 109.2 148.1 138 147.1 112.2 80.2 193 12.1 83 71.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 138.1 95.1 147.2 44.4 200 119.1 185.1 19 103.1 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008106789 0.160227474 -0.009634527
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.179434717 0.003558939 -0.021110084
#> grade_iii, Cure model
#> 0.502831143
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 89 11.44 1 NA 0 0
#> 177 12.53 1 75 0 0
#> 16 8.71 1 71 0 1
#> 166 19.98 1 48 0 0
#> 150 20.33 1 48 0 0
#> 129 23.41 1 53 1 0
#> 127 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 169 22.41 1 46 0 0
#> 99 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 18 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 50 10.02 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 189 10.51 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 16.1 8.71 1 71 0 1
#> 130 16.47 1 53 0 1
#> 199 19.81 1 NA 0 1
#> 199.1 19.81 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 70 7.38 1 30 1 0
#> 69 23.23 1 25 0 1
#> 49 12.19 1 48 1 0
#> 99.1 21.19 1 38 0 1
#> 26 15.77 1 49 0 1
#> 23.1 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 183.1 9.24 1 67 1 0
#> 32 20.90 1 37 1 0
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 179 18.63 1 42 0 0
#> 106 16.67 1 49 1 0
#> 51 18.23 1 83 0 1
#> 42 12.43 1 49 0 1
#> 66 22.13 1 53 0 0
#> 158 20.14 1 74 1 0
#> 91.1 5.33 1 61 0 1
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 69.1 23.23 1 25 0 1
#> 37 12.52 1 57 1 0
#> 86 23.81 1 58 0 1
#> 99.2 21.19 1 38 0 1
#> 189.1 10.51 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 175 21.91 1 43 0 0
#> 106.1 16.67 1 49 1 0
#> 139.1 21.49 1 63 1 0
#> 41 18.02 1 40 1 0
#> 108 18.29 1 39 0 1
#> 100.1 16.07 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 187 9.92 1 39 1 0
#> 99.3 21.19 1 38 0 1
#> 51.1 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 166.1 19.98 1 48 0 0
#> 63 22.77 1 31 1 0
#> 76 19.22 1 54 0 1
#> 55 19.34 1 69 0 1
#> 183.2 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 29 15.45 1 68 1 0
#> 10 10.53 1 34 0 0
#> 166.2 19.98 1 48 0 0
#> 149 8.37 1 33 1 0
#> 181 16.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 180 14.82 1 37 0 0
#> 194 22.40 1 38 0 1
#> 37.1 12.52 1 57 1 0
#> 39 15.59 1 37 0 1
#> 43 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 50.1 10.02 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 23.2 16.92 1 61 0 0
#> 154 12.63 1 20 1 0
#> 10.1 10.53 1 34 0 0
#> 108.1 18.29 1 39 0 1
#> 45 17.42 1 54 0 1
#> 159 10.55 1 50 0 1
#> 56 12.21 1 60 0 0
#> 56.1 12.21 1 60 0 0
#> 195.1 11.76 1 NA 1 0
#> 189.2 10.51 1 NA 1 0
#> 18.1 15.21 1 49 1 0
#> 97.1 19.14 1 65 0 1
#> 58 19.34 1 39 0 0
#> 99.4 21.19 1 38 0 1
#> 100.2 16.07 1 60 0 0
#> 10.2 10.53 1 34 0 0
#> 51.2 18.23 1 83 0 1
#> 61 10.12 1 36 0 1
#> 43.1 12.10 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 42.1 12.43 1 49 0 1
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 41.1 18.02 1 40 1 0
#> 49.1 12.19 1 48 1 0
#> 66.1 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 199.2 19.81 1 NA 0 1
#> 63.1 22.77 1 31 1 0
#> 1 24.00 0 23 1 0
#> 74 24.00 0 43 0 1
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 62 24.00 0 71 0 0
#> 135.1 24.00 0 58 1 0
#> 112 24.00 0 61 0 0
#> 75 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 156.1 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 122 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 148 24.00 0 61 1 0
#> 33 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 147.1 24.00 0 76 1 0
#> 112.1 24.00 0 61 0 0
#> 71 24.00 0 51 0 0
#> 75.1 24.00 0 21 1 0
#> 21 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 9.1 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 53 24.00 0 32 0 1
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 47 24.00 0 38 0 1
#> 27.1 24.00 0 63 1 0
#> 122.1 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 19.1 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 19.2 24.00 0 57 0 1
#> 193 24.00 0 45 0 1
#> 47.1 24.00 0 38 0 1
#> 54.1 24.00 0 53 1 0
#> 94 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 95.1 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 54.2 24.00 0 53 1 0
#> 64.1 24.00 0 43 0 0
#> 74.1 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 109.1 24.00 0 48 0 0
#> 27.2 24.00 0 63 1 0
#> 53.1 24.00 0 32 0 1
#> 116.1 24.00 0 58 0 1
#> 34 24.00 0 36 0 0
#> 19.3 24.00 0 57 0 1
#> 163.1 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 65.1 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 160.1 24.00 0 31 1 0
#> 104.1 24.00 0 50 1 0
#> 161.1 24.00 0 45 0 0
#> 200.1 24.00 0 64 0 0
#> 94.1 24.00 0 51 0 1
#> 11.1 24.00 0 42 0 1
#> 27.3 24.00 0 63 1 0
#> 75.2 24.00 0 21 1 0
#> 132.1 24.00 0 55 0 0
#> 165 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.179 NA NA NA
#> 2 age, Cure model 0.00356 NA NA NA
#> 3 grade_ii, Cure model -0.0211 NA NA NA
#> 4 grade_iii, Cure model 0.503 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00811 NA NA NA
#> 2 grade_ii, Survival model 0.160 NA NA NA
#> 3 grade_iii, Survival model -0.00963 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.179435 0.003559 -0.021110 0.502831
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.179434717 0.003558939 -0.021110084 0.502831143
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008106789 0.160227474 -0.009634527
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78043911 0.80211793 0.94335156 0.43663347 0.41568127 0.10047713
#> [7] 0.99377929 0.61034644 0.19183869 0.30662849 0.92413082 0.74372639
#> [13] 0.38311037 0.28196671 0.77313390 0.94335156 0.66694603 0.62706097
#> [19] 0.96871324 0.12199849 0.85759223 0.30662849 0.71338349 0.62706097
#> [25] 0.68274160 0.46593019 0.69058899 0.92413082 0.36107352 0.98132729
#> [31] 0.72102510 0.53217123 0.65110748 0.55936987 0.83013821 0.22459503
#> [37] 0.42630388 0.98132729 0.26817502 0.97503141 0.12199849 0.81623185
#> [43] 0.03966155 0.30662849 0.36107352 0.25359361 0.65110748 0.28196671
#> [49] 0.58500800 0.54136192 0.69058899 0.46593019 0.91753805 0.30662849
#> [55] 0.55936987 0.40492796 0.43663347 0.15884303 0.50433107 0.48534029
#> [61] 0.92413082 0.07453829 0.73622165 0.89114837 0.43663347 0.95607728
#> [67] 0.67486352 0.78770371 0.76579913 0.20844012 0.81623185 0.72863672
#> [73] 0.87109193 0.51382117 0.95607728 0.62706097 0.79492325 0.89114837
#> [79] 0.54136192 0.61873386 0.88446233 0.84393515 0.84393515 0.74372639
#> [85] 0.51382117 0.48534029 0.30662849 0.69058899 0.89114837 0.55936987
#> [91] 0.91091624 0.87109193 0.80211793 0.83013821 0.60191723 0.75843971
#> [97] 0.58500800 0.85759223 0.22459503 0.39408387 0.15884303 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 60 177 16 166 150 129 127 184 169 99 183 18 190
#> 13.15 12.53 8.71 19.98 20.33 23.41 3.53 17.77 22.41 21.19 9.24 15.21 20.81
#> 139 57 16.1 130 23 70 69 49 99.1 26 23.1 85 170
#> 21.49 14.46 8.71 16.47 16.92 7.38 23.23 12.19 21.19 15.77 16.92 16.44 19.54
#> 100 183.1 32 91 6 179 106 51 42 66 158 91.1 197
#> 16.07 9.24 20.90 5.33 15.64 18.63 16.67 18.23 12.43 22.13 20.14 5.33 21.60
#> 25 69.1 37 86 99.2 32.1 175 106.1 139.1 41 108 100.1 170.1
#> 6.32 23.23 12.52 23.81 21.19 20.90 21.91 16.67 21.49 18.02 18.29 16.07 19.54
#> 187 99.3 51.1 128 166.1 63 76 55 183.2 168 29 10 166.2
#> 9.92 21.19 18.23 20.35 19.98 22.77 19.22 19.34 9.24 23.72 15.45 10.53 19.98
#> 149 181 123 180 194 37.1 39 43 97 149.1 23.2 154 10.1
#> 8.37 16.46 13.00 14.82 22.40 12.52 15.59 12.10 19.14 8.37 16.92 12.63 10.53
#> 108.1 45 159 56 56.1 18.1 97.1 58 99.4 100.2 10.2 51.2 61
#> 18.29 17.42 10.55 12.21 12.21 15.21 19.14 19.34 21.19 16.07 10.53 18.23 10.12
#> 43.1 177.1 42.1 134 157 41.1 49.1 66.1 68 63.1 1 74 104
#> 12.10 12.53 12.43 17.81 15.10 18.02 12.19 22.13 20.62 22.77 24.00 24.00 24.00
#> 28 156 54 163 135 62 135.1 112 75 131 31 156.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 186 9 11 122 147 148 33 33.1 147.1 112.1 71 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 160 126 146 161 9.1 27 38 109 53 84 137 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 27.1 122.1 65 146.1 2 19.1 116 12 19.2 193 47.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 196 3 95 95.1 198 54.2 64.1 74.1 132 109.1 27.2 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 34 19.3 163.1 48 87 17 65.1 67 160.1 104.1 161.1 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 11.1 27.3 75.2 132.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01119323 0.94122791 0.19693715
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.85370540 0.01262229 -0.01119796
#> grade_iii, Cure model
#> 1.41793444
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 99 21.19 1 38 0 1
#> 149 8.37 1 33 1 0
#> 134 17.81 1 47 1 0
#> 139 21.49 1 63 1 0
#> 125 15.65 1 67 1 0
#> 66 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 36 21.19 1 48 0 1
#> 190 20.81 1 42 1 0
#> 68 20.62 1 44 0 0
#> 194.1 22.40 1 38 0 1
#> 170 19.54 1 43 0 1
#> 5 16.43 1 51 0 1
#> 49 12.19 1 48 1 0
#> 99.1 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 61 10.12 1 36 0 1
#> 50 10.02 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 169 22.41 1 46 0 0
#> 99.2 21.19 1 38 0 1
#> 25 6.32 1 34 1 0
#> 125.1 15.65 1 67 1 0
#> 5.1 16.43 1 51 0 1
#> 114 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 85 16.44 1 36 0 0
#> 30 17.43 1 78 0 0
#> 63 22.77 1 31 1 0
#> 63.1 22.77 1 31 1 0
#> 25.1 6.32 1 34 1 0
#> 86 23.81 1 58 0 1
#> 51 18.23 1 83 0 1
#> 169.1 22.41 1 46 0 0
#> 10 10.53 1 34 0 0
#> 99.3 21.19 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 194.2 22.40 1 38 0 1
#> 60 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 140 12.68 1 59 1 0
#> 101 9.97 1 10 0 1
#> 108 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 58 19.34 1 39 0 0
#> 18 15.21 1 49 1 0
#> 8 18.43 1 32 0 0
#> 169.2 22.41 1 46 0 0
#> 180 14.82 1 37 0 0
#> 183 9.24 1 67 1 0
#> 86.1 23.81 1 58 0 1
#> 189.1 10.51 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 86.2 23.81 1 58 0 1
#> 42 12.43 1 49 0 1
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 189.2 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 97 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 69.1 23.23 1 25 0 1
#> 145 10.07 1 65 1 0
#> 164 23.60 1 76 0 1
#> 114.1 13.68 1 NA 0 0
#> 50.1 10.02 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 101.1 9.97 1 10 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 125.2 15.65 1 67 1 0
#> 130 16.47 1 53 0 1
#> 86.3 23.81 1 58 0 1
#> 113 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 55.1 19.34 1 69 0 1
#> 159.1 10.55 1 50 0 1
#> 159.2 10.55 1 50 0 1
#> 60.1 13.15 1 38 1 0
#> 36.1 21.19 1 48 0 1
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 101.2 9.97 1 10 0 1
#> 36.2 21.19 1 48 0 1
#> 50.2 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 190.2 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 180.1 14.82 1 37 0 0
#> 117 17.46 1 26 0 1
#> 68.1 20.62 1 44 0 0
#> 56 12.21 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 45.1 17.42 1 54 0 1
#> 169.3 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 30.1 17.43 1 78 0 0
#> 168.1 23.72 1 70 0 0
#> 168.2 23.72 1 70 0 0
#> 86.4 23.81 1 58 0 1
#> 164.1 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 126 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 3.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 12 24.00 0 63 0 0
#> 185 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 103.1 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 38.1 24.00 0 31 1 0
#> 38.2 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 160 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 165.1 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 103.2 24.00 0 56 1 0
#> 73 24.00 0 NA 0 1
#> 103.3 24.00 0 56 1 0
#> 3.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 137 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 126.1 24.00 0 48 0 0
#> 131.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 53 24.00 0 32 0 1
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 118.2 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 94 24.00 0 51 0 1
#> 131.2 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 48.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 161.2 24.00 0 45 0 0
#> 191.1 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 34.1 24.00 0 36 0 0
#> 3.3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 131.3 24.00 0 66 0 0
#> 12.1 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 98.1 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 21.2 24.00 0 47 0 0
#> 34.2 24.00 0 36 0 0
#> 161.3 24.00 0 45 0 0
#> 172.1 24.00 0 41 0 0
#> 102.1 24.00 0 49 0 0
#> 122 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 19.1 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 22.1 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 118.3 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.854 NA NA NA
#> 2 age, Cure model 0.0126 NA NA NA
#> 3 grade_ii, Cure model -0.0112 NA NA NA
#> 4 grade_iii, Cure model 1.42 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0112 NA NA NA
#> 2 grade_ii, Survival model 0.941 NA NA NA
#> 3 grade_iii, Survival model 0.197 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.85371 0.01262 -0.01120 1.41793
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 241.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.85370540 0.01262229 -0.01119796 1.41793444
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01119323 0.94122791 0.19693715
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.161381122 0.218126411 0.946033880 0.441061496 0.208474271 0.619868285
#> [7] 0.188840148 0.745012944 0.218126411 0.281583787 0.309063072 0.161381122
#> [13] 0.347825038 0.562558996 0.800860234 0.218126411 0.989195500 0.856513847
#> [19] 0.608309323 0.127016478 0.218126411 0.967795560 0.619868285 0.562558996
#> [25] 0.495092658 0.551175543 0.473218229 0.102390461 0.102390461 0.967795560
#> [31] 0.009624730 0.430246305 0.127016478 0.845229060 0.218126411 0.281583787
#> [37] 0.161381122 0.722430391 0.653513693 0.756293546 0.890348337 0.419570429
#> [43] 0.198701771 0.357822773 0.664997947 0.408952127 0.127016478 0.676387585
#> [49] 0.934890835 0.009624730 0.528640483 0.357822773 0.337897943 0.029586481
#> [55] 0.811963384 0.009624730 0.778576531 0.387993756 0.767519861 0.004383623
#> [61] 0.066284139 0.398416193 0.000949102 0.066284139 0.879044576 0.049527729
#> [67] 0.710802156 0.890348337 0.118446076 0.517295514 0.619868285 0.539869538
#> [73] 0.009624730 0.092744768 0.328111485 0.856513847 0.357822773 0.811963384
#> [79] 0.811963384 0.722430391 0.218126411 0.083407051 0.923719723 0.890348337
#> [85] 0.218126411 0.585380862 0.281583787 0.699233828 0.676387585 0.451741938
#> [91] 0.309063072 0.789679938 0.946033880 0.495092658 0.127016478 0.462445114
#> [97] 0.473218229 0.029586481 0.029586481 0.009624730 0.049527729 0.596815101
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 194 99 149 134 139 125 66 123 36 190 68 194.1 170
#> 22.40 21.19 8.37 17.81 21.49 15.65 22.13 13.00 21.19 20.81 20.62 22.40 19.54
#> 5 49 99.1 127 61 26 169 99.2 25 125.1 5.1 45 85
#> 16.43 12.19 21.19 3.53 10.12 15.77 22.41 21.19 6.32 15.65 16.43 17.42 16.44
#> 30 63 63.1 25.1 86 51 169.1 10 99.3 190.1 194.2 60 6
#> 17.43 22.77 22.77 6.32 23.81 18.23 22.41 10.53 21.19 20.81 22.40 13.15 15.64
#> 140 101 108 197 58 18 8 169.2 180 183 86.1 106 55
#> 12.68 9.97 18.29 21.60 19.34 15.21 18.43 22.41 14.82 9.24 23.81 16.67 19.34
#> 105 168 159 86.2 42 76 154 78 69 97 24 69.1 145
#> 19.75 23.72 10.55 23.81 12.43 19.22 12.63 23.88 23.23 19.14 23.89 23.23 10.07
#> 164 81 101.1 15 23 125.2 130 86.3 113 150 61.1 55.1 159.1
#> 23.60 14.06 9.97 22.68 16.92 15.65 16.47 23.81 22.86 20.33 10.12 19.34 10.55
#> 159.2 60.1 36.1 92 187 101.2 36.2 79 190.2 57 180.1 117 68.1
#> 10.55 13.15 21.19 22.92 9.92 9.97 21.19 16.23 20.81 14.46 14.82 17.46 20.62
#> 56 149.1 45.1 169.3 111 30.1 168.1 168.2 86.4 164.1 188 126 103
#> 12.21 8.37 17.42 22.41 17.45 17.43 23.72 23.72 23.81 23.60 16.16 24.00 24.00
#> 38 22 3 165 118 46 19 191 161 3.1 34 102 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 185 47 156 33 103.1 146 38.1 38.2 119 160 176 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 165.1 84 103.2 103.3 3.2 1 118.1 48 138 161.1 137 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1 131.1 11 53 65 146.1 142 176.1 118.2 54 94 131.2 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 152 21 21.1 161.2 191.1 116 174 34.1 3.3 104 121 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.3 12.1 143 143.1 173 98.1 196 21.2 34.2 161.3 172.1 102.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 19.1 2 22.1 64 17 118.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003905245 0.833196913 0.354140315
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.09704164 0.01501667 0.64116175
#> grade_iii, Cure model
#> 1.05084423
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 134 17.81 1 47 1 0
#> 190 20.81 1 42 1 0
#> 192 16.44 1 31 1 0
#> 26 15.77 1 49 0 1
#> 150 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 184 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 5 16.43 1 51 0 1
#> 25 6.32 1 34 1 0
#> 51 18.23 1 83 0 1
#> 184.1 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 10 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 106 16.67 1 49 1 0
#> 79 16.23 1 54 1 0
#> 29 15.45 1 68 1 0
#> 169 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 164 23.60 1 76 0 1
#> 107 11.18 1 54 1 0
#> 197 21.60 1 69 1 0
#> 153 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 123 13.00 1 44 1 0
#> 51.2 18.23 1 83 0 1
#> 125.1 15.65 1 67 1 0
#> 130 16.47 1 53 0 1
#> 41 18.02 1 40 1 0
#> 69 23.23 1 25 0 1
#> 15.1 22.68 1 48 0 0
#> 195.1 11.76 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 41.1 18.02 1 40 1 0
#> 90 20.94 1 50 0 1
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 69.1 23.23 1 25 0 1
#> 49 12.19 1 48 1 0
#> 5.2 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 117 17.46 1 26 0 1
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 4.1 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 187.1 9.92 1 39 1 0
#> 60.1 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 175.1 21.91 1 43 0 0
#> 164.1 23.60 1 76 0 1
#> 171.1 16.57 1 41 0 1
#> 108 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 37 12.52 1 57 1 0
#> 69.2 23.23 1 25 0 1
#> 41.2 18.02 1 40 1 0
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 110.1 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 157.1 15.10 1 47 0 0
#> 134.1 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 187.2 9.92 1 39 1 0
#> 168.1 23.72 1 70 0 0
#> 106.1 16.67 1 49 1 0
#> 23 16.92 1 61 0 0
#> 39 15.59 1 37 0 1
#> 78 23.88 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 154 12.63 1 20 1 0
#> 134.2 17.81 1 47 1 0
#> 110.2 17.56 1 65 0 1
#> 128 20.35 1 35 0 1
#> 187.3 9.92 1 39 1 0
#> 188 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 37.1 12.52 1 57 1 0
#> 99.1 21.19 1 38 0 1
#> 18.1 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 60.2 13.15 1 38 1 0
#> 136 21.83 1 43 0 1
#> 29.1 15.45 1 68 1 0
#> 76 19.22 1 54 0 1
#> 57 14.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 58.1 19.34 1 39 0 0
#> 193 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 102 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 11.1 24.00 0 42 0 1
#> 62 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 173 24.00 0 19 0 1
#> 33.1 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 17 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 33.2 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 152.1 24.00 0 36 0 1
#> 74.1 24.00 0 43 0 1
#> 102.1 24.00 0 49 0 0
#> 103 24.00 0 56 1 0
#> 156.2 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 82 24.00 0 34 0 0
#> 11.2 24.00 0 42 0 1
#> 142 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 146 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#> 20.1 24.00 0 46 1 0
#> 182.1 24.00 0 35 0 0
#> 182.2 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 62.1 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 172.1 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 74.2 24.00 0 43 0 1
#> 172.2 24.00 0 41 0 0
#> 3.1 24.00 0 31 1 0
#> 102.2 24.00 0 49 0 0
#> 72 24.00 0 40 0 1
#> 144.1 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 198 24.00 0 66 0 1
#> 11.3 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 27.1 24.00 0 63 1 0
#> 27.2 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 71 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.10 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model 0.641 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00391 NA NA NA
#> 2 grade_ii, Survival model 0.833 NA NA NA
#> 3 grade_iii, Survival model 0.354 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09704 0.01502 0.64116 1.05084
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 251.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09704164 0.01501667 0.64116175 1.05084423
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003905245 0.833196913 0.354140315
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.612042316 0.495193564 0.333819358 0.646992213 0.705976683 0.354473827
#> [7] 0.714316199 0.540336079 0.893096952 0.522131926 0.907802846 0.655612139
#> [13] 0.993058977 0.436727620 0.522131926 0.279784459 0.929647991 0.197043979
#> [19] 0.594490462 0.680968097 0.755100533 0.220228375 0.885729482 0.680968097
#> [25] 0.436727620 0.025803368 0.075646278 0.915121294 0.268112818 0.291079783
#> [31] 0.416069542 0.174319138 0.825723299 0.855989273 0.436727620 0.714316199
#> [37] 0.629487088 0.466845106 0.123389162 0.197043979 0.922389567 0.466845106
#> [43] 0.323138637 0.951374191 0.810046662 0.655612139 0.770969358 0.123389162
#> [49] 0.900477139 0.655612139 0.302012077 0.979072978 0.567268942 0.375206074
#> [55] 0.944165560 0.786549594 0.848366700 0.232249939 0.160648592 0.951374191
#> [61] 0.825723299 0.730606344 0.232249939 0.075646278 0.612042316 0.426426551
#> [67] 0.107971035 0.871034307 0.123389162 0.466845106 0.364814769 0.638251370
#> [73] 0.540336079 0.042741010 0.746993118 0.786549594 0.495193564 0.986068380
#> [79] 0.802181763 0.951374191 0.042741010 0.594490462 0.585405608 0.738810327
#> [85] 0.007906273 0.174319138 0.863548741 0.495193564 0.540336079 0.344184213
#> [91] 0.951374191 0.697619717 0.576350543 0.871034307 0.302012077 0.770969358
#> [97] 0.375206074 0.825723299 0.256043476 0.755100533 0.405685277 0.817892316
#> [103] 0.936913470 0.375206074 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 171 134 190 192 26 150 125 110 56 184 43 5 25
#> 16.57 17.81 20.81 16.44 15.77 20.33 15.65 17.56 12.21 17.77 12.10 16.43 6.32
#> 51 184.1 139 10 15 106 79 29 169 42 79.1 51.1 86
#> 18.23 17.77 21.49 10.53 22.68 16.67 16.23 15.45 22.41 12.43 16.23 18.23 23.81
#> 164 107 197 153 97 63 60 123 51.2 125.1 130 41 69
#> 23.60 11.18 21.60 21.33 19.14 22.77 13.15 13.00 18.23 15.65 16.47 18.02 23.23
#> 15.1 159 41.1 90 187 96 5.1 18 69.1 49 5.2 99 16
#> 22.68 10.55 18.02 20.94 9.92 14.54 16.43 15.21 23.23 12.19 16.43 21.19 8.71
#> 117 55 145 157 155 175 113 187.1 60.1 6 175.1 164.1 171.1
#> 17.46 19.34 10.07 15.10 13.08 21.91 22.86 9.92 13.15 15.64 21.91 23.60 16.57
#> 108 129 37 69.2 41.2 166 181 110.1 168 167 157.1 134.1 77
#> 18.29 23.41 12.52 23.23 18.02 19.98 16.46 17.56 23.72 15.55 15.10 17.81 7.27
#> 180 187.2 168.1 106.1 23 39 78 63.1 154 134.2 110.2 128 187.3
#> 14.82 9.92 23.72 16.67 16.92 15.59 23.88 22.77 12.63 17.81 17.56 20.35 9.92
#> 188 111 37.1 99.1 18.1 58 60.2 136 29.1 76 57 61 58.1
#> 16.16 17.45 12.52 21.19 15.21 19.34 13.15 21.83 15.45 19.22 14.46 10.12 19.34
#> 193 34 196 102 182 11 186 116 1 48 186.1 3 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 1.1 33 143 34.1 126 11.1 62 152 131 138 160 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 147 173 33.1 121 156 156.1 109 132 17 17.1 33.2 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 178 87 152.1 74.1 102.1 103 156.2 141.1 172 54 161 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 82 11.2 142 165 144 53 146 54.1 20.1 182.1 182.2 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 135 172.1 27 74.2 172.2 3.1 102.2 72 144.1 198 11.3 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 27.1 27.2 94 9 75 71 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01430785 0.28944944 0.57871947
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.69339433 0.00801881 0.36136856
#> grade_iii, Cure model
#> 1.03483250
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 184 17.77 1 38 0 0
#> 181 16.46 1 45 0 1
#> 129 23.41 1 53 1 0
#> 153 21.33 1 55 1 0
#> 180 14.82 1 37 0 0
#> 97 19.14 1 65 0 1
#> 181.1 16.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 139 21.49 1 63 1 0
#> 93 10.33 1 52 0 1
#> 58 19.34 1 39 0 0
#> 150 20.33 1 48 0 0
#> 91 5.33 1 61 0 1
#> 158 20.14 1 74 1 0
#> 97.1 19.14 1 65 0 1
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 113 22.86 1 34 0 0
#> 25 6.32 1 34 1 0
#> 43 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 57 14.46 1 45 0 1
#> 4.1 17.64 1 NA 0 1
#> 16.1 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 60.1 13.15 1 38 1 0
#> 39 15.59 1 37 0 1
#> 92 22.92 1 47 0 1
#> 123 13.00 1 44 1 0
#> 155 13.08 1 26 0 0
#> 23 16.92 1 61 0 0
#> 4.2 17.64 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 194 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 63 22.77 1 31 1 0
#> 43.1 12.10 1 61 0 1
#> 43.2 12.10 1 61 0 1
#> 69 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 111.1 17.45 1 47 0 1
#> 26 15.77 1 49 0 1
#> 170 19.54 1 43 0 1
#> 168 23.72 1 70 0 0
#> 90 20.94 1 50 0 1
#> 60.2 13.15 1 38 1 0
#> 158.1 20.14 1 74 1 0
#> 159 10.55 1 50 0 1
#> 63.1 22.77 1 31 1 0
#> 55 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 39.1 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 195 11.76 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 159.2 10.55 1 50 0 1
#> 107 11.18 1 54 1 0
#> 63.2 22.77 1 31 1 0
#> 16.2 8.71 1 71 0 1
#> 158.2 20.14 1 74 1 0
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 58.1 19.34 1 39 0 0
#> 30.1 17.43 1 78 0 0
#> 123.1 13.00 1 44 1 0
#> 136 21.83 1 43 0 1
#> 43.3 12.10 1 61 0 1
#> 97.2 19.14 1 65 0 1
#> 70 7.38 1 30 1 0
#> 49 12.19 1 48 1 0
#> 45 17.42 1 54 0 1
#> 68 20.62 1 44 0 0
#> 68.1 20.62 1 44 0 0
#> 97.3 19.14 1 65 0 1
#> 23.1 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 56.1 12.21 1 60 0 0
#> 155.1 13.08 1 26 0 0
#> 195.1 11.76 1 NA 1 0
#> 181.2 16.46 1 45 0 1
#> 170.1 19.54 1 43 0 1
#> 63.3 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 25.1 6.32 1 34 1 0
#> 59 10.16 1 NA 1 0
#> 58.2 19.34 1 39 0 0
#> 189 10.51 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 39.2 15.59 1 37 0 1
#> 90.1 20.94 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 45.1 17.42 1 54 0 1
#> 167.1 15.55 1 56 1 0
#> 171 16.57 1 41 0 1
#> 86 23.81 1 58 0 1
#> 30.2 17.43 1 78 0 0
#> 166 19.98 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 148 24.00 0 61 1 0
#> 185 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 142 24.00 0 53 0 0
#> 71.1 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 54 24.00 0 53 1 0
#> 72 24.00 0 40 0 1
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 143 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 104 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 162.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 193.1 24.00 0 45 0 1
#> 118 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 103 24.00 0 56 1 0
#> 116 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 165.2 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 132.1 24.00 0 55 0 0
#> 54.1 24.00 0 53 1 0
#> 62.1 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 62.2 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 72.1 24.00 0 40 0 1
#> 156 24.00 0 50 1 0
#> 173.1 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 1.1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 193.2 24.00 0 45 0 1
#> 71.2 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 9.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 44.1 24.00 0 56 0 0
#> 119.1 24.00 0 17 0 0
#> 162.2 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 19.1 24.00 0 57 0 1
#> 95 24.00 0 68 0 1
#> 198.1 24.00 0 66 0 1
#> 115.1 24.00 0 NA 1 0
#> 142.1 24.00 0 53 0 0
#> 19.2 24.00 0 57 0 1
#> 198.2 24.00 0 66 0 1
#> 178.1 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 62.3 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 71.3 24.00 0 51 0 0
#> 193.3 24.00 0 45 0 1
#> 104.2 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 44.2 24.00 0 56 0 0
#> 119.2 24.00 0 17 0 0
#> 142.2 24.00 0 53 0 0
#> 151.1 24.00 0 42 0 0
#> 9.2 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 141 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.693 NA NA NA
#> 2 age, Cure model 0.00802 NA NA NA
#> 3 grade_ii, Cure model 0.361 NA NA NA
#> 4 grade_iii, Cure model 1.03 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0143 NA NA NA
#> 2 grade_ii, Survival model 0.289 NA NA NA
#> 3 grade_iii, Survival model 0.579 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.693394 0.008019 0.361369 1.034832
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 248.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69339433 0.00801881 0.36136856 1.03483250
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01430785 0.28944944 0.57871947
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7641008 0.8229533 0.3450041 0.5556402 0.8738486 0.7157286 0.8229533
#> [8] 0.7699653 0.9764784 0.5441859 0.9693822 0.6880540 0.6150829 0.9966850
#> [15] 0.6331968 0.7157286 0.7812233 0.8782493 0.9241584 0.8869183 0.1322836
#> [22] 0.4374730 0.9899933 0.9361588 0.6652718 0.6150829 0.8911682 0.8826093
#> [29] 0.9764784 0.1322836 0.8911682 0.8468775 0.4212156 0.9119167 0.9036264
#> [36] 0.8077145 0.8605080 0.5194569 0.5060852 0.4533605 0.9361588 0.9361588
#> [43] 0.3860060 0.7582037 0.7462117 0.9729431 0.8373614 0.3860060 0.7699653
#> [50] 0.8421543 0.6731628 0.3176540 0.5666554 0.8911682 0.6331968 0.9549221
#> [57] 0.4533605 0.6880540 0.6056830 0.8468775 0.7522314 0.9549221 0.9549221
#> [64] 0.9511740 0.4533605 0.9764784 0.6331968 0.8694325 0.7400874 0.6880540
#> [71] 0.7812233 0.9119167 0.5321515 0.9361588 0.7157286 0.9866150 0.9321718
#> [78] 0.7973371 0.5864537 0.5864537 0.7157286 0.8077145 0.9200950 0.9241584
#> [85] 0.9036264 0.8229533 0.6731628 0.4533605 0.2364047 0.9899933 0.6880540
#> [92] 0.9657849 0.8468775 0.5666554 0.3450041 0.7973371 0.8605080 0.8179094
#> [99] 0.2855477 0.7812233 0.6572515 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 184 181 129 153 180 97 181.1 111 16 139 93 58 150
#> 17.77 16.46 23.41 21.33 14.82 19.14 16.46 17.45 8.71 21.49 10.33 19.34 20.33
#> 91 158 97.1 30 96 56 13 24 113 25 43 105 150.1
#> 5.33 20.14 19.14 17.43 14.54 12.21 14.34 23.89 22.86 6.32 12.10 19.75 20.33
#> 60 57 16.1 24.1 60.1 39 92 123 155 23 167 194 15
#> 13.15 14.46 8.71 23.89 13.15 15.59 22.92 13.00 13.08 16.92 15.55 22.40 22.68
#> 63 43.1 43.2 69 134 108 61 100 69.1 111.1 26 170 168
#> 22.77 12.10 12.10 23.23 17.81 18.29 10.12 16.07 23.23 17.45 15.77 19.54 23.72
#> 90 60.2 158.1 159 63.1 55 128 39.1 40 159.1 159.2 107 63.2
#> 20.94 13.15 20.14 10.55 22.77 19.34 20.35 15.59 18.00 10.55 10.55 11.18 22.77
#> 16.2 158.2 29 179 58.1 30.1 123.1 136 43.3 97.2 70 49 45
#> 8.71 20.14 15.45 18.63 19.34 17.43 13.00 21.83 12.10 19.14 7.38 12.19 17.42
#> 68 68.1 97.3 23.1 177 56.1 155.1 181.2 170.1 63.3 78 25.1 58.2
#> 20.62 20.62 19.14 16.92 12.53 12.21 13.08 16.46 19.54 22.77 23.88 6.32 19.34
#> 52 39.2 90.1 129.1 45.1 167.1 171 86 30.2 166 148 185 151
#> 10.42 15.59 20.94 23.41 17.42 15.55 16.57 23.81 17.43 19.98 24.00 24.00 24.00
#> 71 1 65 27 198 142 71.1 132 54 72 161 193 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 112 104 160 162 44 162.1 2 193.1 118 165 176 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 17 62 131 131.1 19 103 116 191 165.2 178 87 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 62.1 173 62.2 120 72.1 156 173.1 126 1.1 9 146 193.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 11 9.1 119 44.1 119.1 162.2 104.1 19.1 95 198.1 142.1 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.2 178.1 122 62.3 135 71.3 193.3 104.2 83 102 44.2 119.2 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 9.2 38 102.1 141
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004122621 0.5614254849 0.1068093655
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05648327 0.02172498 -0.06311478
#> grade_iii, Cure model
#> 0.70405142
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 57 14.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 29 15.45 1 68 1 0
#> 139.1 21.49 1 63 1 0
#> 18 15.21 1 49 1 0
#> 29.1 15.45 1 68 1 0
#> 66 22.13 1 53 0 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 41 18.02 1 40 1 0
#> 10 10.53 1 34 0 0
#> 117 17.46 1 26 0 1
#> 6.1 15.64 1 39 0 0
#> 41.1 18.02 1 40 1 0
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 108 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 69 23.23 1 25 0 1
#> 52 10.42 1 52 0 1
#> 140 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 169.1 22.41 1 46 0 0
#> 59.1 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 149 8.37 1 33 1 0
#> 199 19.81 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 105 19.75 1 60 0 0
#> 97 19.14 1 65 0 1
#> 56 12.21 1 60 0 0
#> 108.1 18.29 1 39 0 1
#> 56.1 12.21 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 188.1 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 93 10.33 1 52 0 1
#> 69.1 23.23 1 25 0 1
#> 58 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 189.1 10.51 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 37.1 12.52 1 57 1 0
#> 169.2 22.41 1 46 0 0
#> 189.2 10.51 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 164 23.60 1 76 0 1
#> 99 21.19 1 38 0 1
#> 125 15.65 1 67 1 0
#> 55 19.34 1 69 0 1
#> 41.2 18.02 1 40 1 0
#> 52.1 10.42 1 52 0 1
#> 92 22.92 1 47 0 1
#> 39 15.59 1 37 0 1
#> 60 13.15 1 38 1 0
#> 32 20.90 1 37 1 0
#> 37.2 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 10.1 10.53 1 34 0 0
#> 192 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 97.1 19.14 1 65 0 1
#> 60.1 13.15 1 38 1 0
#> 41.3 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 128 20.35 1 35 0 1
#> 88.2 18.37 1 47 0 0
#> 130 16.47 1 53 0 1
#> 105.1 19.75 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 99.1 21.19 1 38 0 1
#> 171 16.57 1 41 0 1
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 169.3 22.41 1 46 0 0
#> 66.1 22.13 1 53 0 0
#> 10.2 10.53 1 34 0 0
#> 183 9.24 1 67 1 0
#> 192.1 16.44 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 86 23.81 1 58 0 1
#> 81 14.06 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 129 23.41 1 53 1 0
#> 26 15.77 1 49 0 1
#> 111.1 17.45 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 117.2 17.46 1 26 0 1
#> 76.1 19.22 1 54 0 1
#> 128.1 20.35 1 35 0 1
#> 85 16.44 1 36 0 0
#> 13 14.34 1 54 0 1
#> 179 18.63 1 42 0 0
#> 177 12.53 1 75 0 0
#> 39.1 15.59 1 37 0 1
#> 159 10.55 1 50 0 1
#> 6.2 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 15 22.68 1 48 0 0
#> 106 16.67 1 49 1 0
#> 199.1 19.81 1 NA 0 1
#> 187.1 9.92 1 39 1 0
#> 37.3 12.52 1 57 1 0
#> 42 12.43 1 49 0 1
#> 177.1 12.53 1 75 0 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 116.1 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 82 24.00 0 34 0 0
#> 161 24.00 0 45 0 0
#> 71 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 87 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 7 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 116.2 24.00 0 58 0 1
#> 132.1 24.00 0 55 0 0
#> 17 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 132.2 24.00 0 55 0 0
#> 71.1 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 146.1 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 163.1 24.00 0 66 0 0
#> 75.1 24.00 0 21 1 0
#> 138.1 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 160.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 9.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 31.1 24.00 0 36 0 1
#> 126.1 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 9.2 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 137.1 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 104.1 24.00 0 50 1 0
#> 9.3 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 17.1 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 44.1 24.00 0 56 0 0
#> 33 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 176.1 24.00 0 43 0 1
#> 116.3 24.00 0 58 0 1
#> 193.1 24.00 0 45 0 1
#> 119 24.00 0 17 0 0
#> 161.1 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0217 NA NA NA
#> 3 grade_ii, Cure model -0.0631 NA NA NA
#> 4 grade_iii, Cure model 0.704 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000412 NA NA NA
#> 2 grade_ii, Survival model 0.561 NA NA NA
#> 3 grade_iii, Survival model 0.107 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05648 0.02172 -0.06311 0.70405
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 253.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05648327 0.02172498 -0.06311478 0.70405142
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004122621 0.5614254849 0.1068093655
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.12955977 0.20103558 0.74951828 0.66256176 0.71524765 0.20103558
#> [7] 0.73240378 0.71524765 0.17597315 0.99226402 0.31851744 0.46101797
#> [13] 0.88111993 0.49823954 0.66256176 0.46101797 0.81682671 0.93744034
#> [19] 0.43056339 0.40043450 0.07741280 0.90519533 0.79187306 0.52626543
#> [25] 0.12955977 0.60903552 0.97684219 0.74096028 0.49823954 0.29792680
#> [31] 0.36984408 0.85689290 0.43056339 0.85689290 0.40043450 0.60903552
#> [37] 0.60002163 0.92129206 0.07741280 0.32895283 0.22407015 0.45080063
#> [43] 0.81682671 0.12955977 0.22407015 0.04588103 0.24553279 0.65368163
#> [49] 0.32895283 0.46101797 0.90519533 0.10273472 0.68886346 0.77514960
#> [55] 0.26681917 0.81682671 0.34945103 0.88111993 0.57309952 0.92936958
#> [61] 0.36984408 0.77514960 0.46101797 0.62688180 0.27737143 0.40043450
#> [67] 0.56376637 0.29792680 0.97684219 0.24553279 0.55441951 0.95331995
#> [73] 0.01025102 0.12955977 0.17597315 0.88111993 0.96901004 0.57309952
#> [79] 0.93744034 0.02830864 0.76660777 0.06302831 0.63587252 0.52626543
#> [85] 0.63587252 0.49823954 0.34945103 0.27737143 0.57309952 0.75806727
#> [91] 0.39014419 0.80021644 0.68886346 0.87302369 0.66256176 0.70646824
#> [97] 0.11613122 0.54505781 0.95331995 0.81682671 0.84879293 0.80021644
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 169 139 57 6 29 139.1 18 29.1 66 91 170 41 10
#> 22.41 21.49 14.46 15.64 15.45 21.49 15.21 15.45 22.13 5.33 19.54 18.02 10.53
#> 117 6.1 41.1 37 145 108 88 69 52 140 111 169.1 188
#> 17.46 15.64 18.02 12.52 10.07 18.29 18.37 23.23 10.42 12.68 17.45 22.41 16.16
#> 149 180 117.1 105 97 56 108.1 56.1 88.1 188.1 79 93 69.1
#> 8.37 14.82 17.46 19.75 19.14 12.21 18.29 12.21 18.37 16.16 16.23 10.33 23.23
#> 58 153 51 37.1 169.2 153.1 164 99 125 55 41.2 52.1 92
#> 19.34 21.33 18.23 12.52 22.41 21.33 23.60 21.19 15.65 19.34 18.02 10.42 22.92
#> 39 60 32 37.2 76 10.1 192 61 97.1 60.1 41.3 100 128
#> 15.59 13.15 20.90 12.52 19.22 10.53 16.44 10.12 19.14 13.15 18.02 16.07 20.35
#> 88.2 130 105.1 149.1 99.1 171 187 24 169.3 66.1 10.2 183 192.1
#> 18.37 16.47 19.75 8.37 21.19 16.57 9.92 23.89 22.41 22.13 10.53 9.24 16.44
#> 145.1 86 81 129 26 111.1 26.1 117.2 76.1 128.1 85 13 179
#> 10.07 23.81 14.06 23.41 15.77 17.45 15.77 17.46 19.22 20.35 16.44 14.34 18.63
#> 177 39.1 159 6.2 167 15 106 187.1 37.3 42 177.1 75 135
#> 12.53 15.59 10.55 15.64 15.55 22.68 16.67 9.92 12.52 12.43 12.53 24.00 24.00
#> 48 34 132 38 46 174 116 116.1 21 20 163 160 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 152 31 162 146 82 161 71 178 94 87 138 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 7 64 172 116.2 132.1 17 137 132.2 71.1 9 185 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 94.1 176 53 146.1 2 163.1 75.1 138.1 144 160.1 28 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 172.1 156 193 31.1 126.1 38.1 46.1 174.1 9.2 185.1 178.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 1 65 80 104.1 9.3 156.1 182 17.1 120 44.1 33 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 116.3 193.1 119 161.1 3 20.1 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005087251 0.407538481 0.369362413
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.502519744 0.008988938 0.253662391
#> grade_iii, Cure model
#> 0.706449369
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 175 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 133 14.65 1 57 0 0
#> 133.1 14.65 1 57 0 0
#> 56 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 43 12.10 1 61 0 1
#> 68 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 194 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 180 14.82 1 37 0 0
#> 4 17.64 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 97 19.14 1 65 0 1
#> 150 20.33 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 4.1 17.64 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 127 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 99 21.19 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 134 17.81 1 47 1 0
#> 13.1 14.34 1 54 0 1
#> 25 6.32 1 34 1 0
#> 97.1 19.14 1 65 0 1
#> 60 13.15 1 38 1 0
#> 125.1 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 180.1 14.82 1 37 0 0
#> 134.1 17.81 1 47 1 0
#> 88.1 18.37 1 47 0 0
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 154 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 36 21.19 1 48 0 1
#> 97.2 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 133.2 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 175.1 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 18 15.21 1 49 1 0
#> 4.2 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 187.1 9.92 1 39 1 0
#> 124 9.73 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 59.1 10.16 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 157 15.10 1 47 0 0
#> 29.1 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 93 10.33 1 52 0 1
#> 130 16.47 1 53 0 1
#> 18.1 15.21 1 49 1 0
#> 154.1 12.63 1 20 1 0
#> 15 22.68 1 48 0 0
#> 18.2 15.21 1 49 1 0
#> 197 21.60 1 69 1 0
#> 51 18.23 1 83 0 1
#> 13.2 14.34 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 16 8.71 1 71 0 1
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 153 21.33 1 55 1 0
#> 91.1 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 32 20.90 1 37 1 0
#> 88.2 18.37 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 145 10.07 1 65 1 0
#> 169 22.41 1 46 0 0
#> 153.1 21.33 1 55 1 0
#> 60.1 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 166 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 166.1 19.98 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 91.2 5.33 1 61 0 1
#> 24.1 23.89 1 38 0 0
#> 41 18.02 1 40 1 0
#> 39 15.59 1 37 0 1
#> 195.1 11.76 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 57.1 14.46 1 45 0 1
#> 180.2 14.82 1 37 0 0
#> 89.1 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 194.1 22.40 1 38 0 1
#> 155.1 13.08 1 26 0 0
#> 13.3 14.34 1 54 0 1
#> 5 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 105.1 19.75 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 156 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 104 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 193 24.00 0 45 0 1
#> 74 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 137 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 74.1 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 142.1 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 119 24.00 0 17 0 0
#> 156.1 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 119.1 24.00 0 17 0 0
#> 103 24.00 0 56 1 0
#> 102 24.00 0 49 0 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 65 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 75 24.00 0 21 1 0
#> 95 24.00 0 68 0 1
#> 109.2 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 98 24.00 0 34 1 0
#> 11 24.00 0 42 0 1
#> 143 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 193.1 24.00 0 45 0 1
#> 74.2 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 163 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 48.1 24.00 0 31 1 0
#> 103.2 24.00 0 56 1 0
#> 102.1 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 151 24.00 0 42 0 0
#> 115.1 24.00 0 NA 1 0
#> 7.1 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 67 24.00 0 25 0 0
#> 148.1 24.00 0 61 1 0
#> 118 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 73.1 24.00 0 NA 0 1
#> 131 24.00 0 66 0 0
#> 115.2 24.00 0 NA 1 0
#> 131.1 24.00 0 66 0 0
#> 109.3 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 64.1 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 2.1 24.00 0 9 0 0
#> 173 24.00 0 19 0 1
#> 142.2 24.00 0 53 0 0
#> 103.3 24.00 0 56 1 0
#> 44.1 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 119.2 24.00 0 17 0 0
#> 72.1 24.00 0 40 0 1
#> 73.2 24.00 0 NA 0 1
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 73.3 24.00 0 NA 0 1
#> 142.3 24.00 0 53 0 0
#> 44.2 24.00 0 56 0 0
#> 47.1 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 143.1 24.00 0 51 0 0
#> 73.4 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.503 NA NA NA
#> 2 age, Cure model 0.00899 NA NA NA
#> 3 grade_ii, Cure model 0.254 NA NA NA
#> 4 grade_iii, Cure model 0.706 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00509 NA NA NA
#> 2 grade_ii, Survival model 0.408 NA NA NA
#> 3 grade_iii, Survival model 0.369 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.502520 0.008989 0.253662 0.706449
#>
#> Degrees of Freedom: 178 Total (i.e. Null); 175 Residual
#> Null Deviance: 246.1
#> Residual Deviance: 241.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.502519744 0.008988938 0.253662391 0.706449369
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005087251 0.407538481 0.369362413
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.88127637 0.61921271 0.95167819 0.25617058 0.93296592 0.75795359
#> [7] 0.75795359 0.89440824 0.80068258 0.90093633 0.37450652 0.04528556
#> [13] 0.48186150 0.22531604 0.66859004 0.73627424 0.84801902 0.44156044
#> [19] 0.38605613 0.78660343 0.97618806 0.99404646 0.55787319 0.30066396
#> [25] 0.33935697 0.57598495 0.53975322 0.80068258 0.96402870 0.44156044
#> [31] 0.83457898 0.66859004 0.57598495 0.73627424 0.53975322 0.48186150
#> [37] 0.15329381 0.82774062 0.86810659 0.64426388 0.33935697 0.44156044
#> [43] 0.47164977 0.75795359 0.12980693 0.25617058 0.92662867 0.70706145
#> [49] 0.77942639 0.93296592 0.88786309 0.65244034 0.60212273 0.69197024
#> [55] 0.72893047 0.69197024 0.86142900 0.90741871 0.61072120 0.70706145
#> [61] 0.86810659 0.18907824 0.70706145 0.28614757 0.51135694 0.80068258
#> [67] 0.51135694 0.94545651 0.10325587 0.66053281 0.31446687 0.97618806
#> [73] 0.56697618 0.62760992 0.36286689 0.48186150 0.96402870 0.92026870
#> [79] 0.20740515 0.31446687 0.83457898 0.41974177 0.39751098 0.15329381
#> [85] 0.39751098 0.97618806 0.04528556 0.53032576 0.68419124 0.59340872
#> [91] 0.78660343 0.73627424 0.91386036 0.22531604 0.84801902 0.80068258
#> [97] 0.63598462 0.95786840 0.41974177 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 177 181 149 175 187 133 133.1 56 13 43 68 24 88
#> 12.53 16.46 8.37 21.91 9.92 14.65 14.65 12.21 14.34 12.10 20.62 23.89 18.37
#> 194 125 180 155 97 150 57 91 127 184 139 99 111
#> 22.40 15.65 14.82 13.08 19.14 20.33 14.46 5.33 3.53 17.77 21.49 21.19 17.45
#> 134 13.1 25 97.1 60 125.1 111.1 180.1 134.1 88.1 63 81 154
#> 17.81 14.34 6.32 19.14 13.15 15.65 17.45 14.82 17.81 18.37 22.77 14.06 12.63
#> 79 36 97.2 8 133.2 69 175.1 101 18 96 187.1 42 188
#> 16.23 21.19 19.14 18.43 14.65 23.23 21.91 9.97 15.21 14.54 9.92 12.43 16.16
#> 106 29 157 29.1 140 93 130 18.1 154.1 15 18.2 197 51
#> 16.67 15.45 15.10 15.45 12.68 10.33 16.47 15.21 12.63 22.68 15.21 21.60 18.23
#> 13.2 51.1 16 86 100 153 91.1 117 85 32 88.2 25.1 145
#> 14.34 18.23 8.71 23.81 16.07 21.33 5.33 17.46 16.44 20.90 18.37 6.32 10.07
#> 169 153.1 60.1 105 166 63.1 166.1 91.2 24.1 41 39 30 57.1
#> 22.41 21.33 13.15 19.75 19.98 22.77 19.98 5.33 23.89 18.02 15.59 17.43 14.46
#> 180.2 61 194.1 155.1 13.3 5 70 105.1 156 144 104 193 74
#> 14.82 10.12 22.40 13.08 14.34 16.43 7.38 19.75 24.00 24.00 24.00 24.00 24.00
#> 196 137 121 48 7 142 74.1 116 109 22 22.1 33 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 109.1 200 119 156.1 35 119.1 103 102 160 146 44 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 75 95 109.2 191 2 98 11 143 19 193.1 74.2 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 95.1 48.1 103.2 102.1 174 151 7.1 64 67 148.1 118 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 131.1 109.3 47 21 64.1 72 2.1 173 142.2 103.3 44.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.2 72.1 12 112 142.3 44.2 47.1 146.1 67.1 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00494349 0.17274904 0.09810199
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06568417 0.01351671 0.63876050
#> grade_iii, Cure model
#> 1.29985215
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 187 9.92 1 39 1 0
#> 123 13.00 1 44 1 0
#> 37 12.52 1 57 1 0
#> 155 13.08 1 26 0 0
#> 133 14.65 1 57 0 0
#> 166 19.98 1 48 0 0
#> 68 20.62 1 44 0 0
#> 50 10.02 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 69 23.23 1 25 0 1
#> 77 7.27 1 67 0 1
#> 189 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 171 16.57 1 41 0 1
#> 8 18.43 1 32 0 0
#> 85 16.44 1 36 0 0
#> 129 23.41 1 53 1 0
#> 57 14.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 93 10.33 1 52 0 1
#> 181 16.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 23 16.92 1 61 0 0
#> 154 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 154.1 12.63 1 20 1 0
#> 88 18.37 1 47 0 0
#> 107 11.18 1 54 1 0
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 136.1 21.83 1 43 0 1
#> 194 22.40 1 38 0 1
#> 66 22.13 1 53 0 0
#> 4 17.64 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 69.1 23.23 1 25 0 1
#> 180 14.82 1 37 0 0
#> 197 21.60 1 69 1 0
#> 40 18.00 1 28 1 0
#> 181.1 16.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 157 15.10 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 79.1 16.23 1 54 1 0
#> 58 19.34 1 39 0 0
#> 187.1 9.92 1 39 1 0
#> 50.1 10.02 1 NA 1 0
#> 129.2 23.41 1 53 1 0
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 100 16.07 1 60 0 0
#> 145 10.07 1 65 1 0
#> 77.1 7.27 1 67 0 1
#> 97 19.14 1 65 0 1
#> 5 16.43 1 51 0 1
#> 4.1 17.64 1 NA 0 1
#> 111.1 17.45 1 47 0 1
#> 23.1 16.92 1 61 0 0
#> 189.1 10.51 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 91 5.33 1 61 0 1
#> 188 16.16 1 46 0 1
#> 93.1 10.33 1 52 0 1
#> 52 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 189.2 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 77.2 7.27 1 67 0 1
#> 189.3 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 177 12.53 1 75 0 0
#> 183 9.24 1 67 1 0
#> 133.2 14.65 1 57 0 0
#> 68.1 20.62 1 44 0 0
#> 180.1 14.82 1 37 0 0
#> 139 21.49 1 63 1 0
#> 150.1 20.33 1 48 0 0
#> 49 12.19 1 48 1 0
#> 153 21.33 1 55 1 0
#> 29.1 15.45 1 68 1 0
#> 197.1 21.60 1 69 1 0
#> 37.2 12.52 1 57 1 0
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 164 23.60 1 76 0 1
#> 89 11.44 1 NA 0 0
#> 77.3 7.27 1 67 0 1
#> 117.1 17.46 1 26 0 1
#> 111.2 17.45 1 47 0 1
#> 15 22.68 1 48 0 0
#> 167.1 15.55 1 56 1 0
#> 24 23.89 1 38 0 0
#> 167.2 15.55 1 56 1 0
#> 139.1 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 197.2 21.60 1 69 1 0
#> 96.1 14.54 1 33 0 1
#> 88.1 18.37 1 47 0 0
#> 171.1 16.57 1 41 0 1
#> 179 18.63 1 42 0 0
#> 40.1 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 171.2 16.57 1 41 0 1
#> 181.2 16.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 136.2 21.83 1 43 0 1
#> 108 18.29 1 39 0 1
#> 107.1 11.18 1 54 1 0
#> 111.3 17.45 1 47 0 1
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 102 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 148 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 98.1 24.00 0 34 1 0
#> 115 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 115.1 24.00 0 NA 1 0
#> 44 24.00 0 56 0 0
#> 137 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 144 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 143.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 95.1 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 172 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 102.1 24.00 0 49 0 0
#> 27.1 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 141.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 151 24.00 0 42 0 0
#> 64 24.00 0 43 0 0
#> 46 24.00 0 71 0 0
#> 27.2 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 102.2 24.00 0 49 0 0
#> 67 24.00 0 25 0 0
#> 162.1 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 119 24.00 0 17 0 0
#> 137.1 24.00 0 45 1 0
#> 21.1 24.00 0 47 0 0
#> 151.1 24.00 0 42 0 0
#> 132.1 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 132.2 24.00 0 55 0 0
#> 186.1 24.00 0 45 1 0
#> 53.1 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 87.1 24.00 0 27 0 0
#> 112.1 24.00 0 61 0 0
#> 65 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 198.1 24.00 0 66 0 1
#> 173 24.00 0 19 0 1
#> 95.2 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 64.2 24.00 0 43 0 0
#> 174 24.00 0 49 1 0
#> 102.3 24.00 0 49 0 0
#> 141.2 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 82.2 24.00 0 34 0 0
#> 142.1 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 46.1 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.07 NA NA NA
#> 2 age, Cure model 0.0135 NA NA NA
#> 3 grade_ii, Cure model 0.639 NA NA NA
#> 4 grade_iii, Cure model 1.30 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00494 NA NA NA
#> 2 grade_ii, Survival model 0.173 NA NA NA
#> 3 grade_iii, Survival model 0.0981 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06568 0.01352 0.63876 1.29985
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06568417 0.01351671 0.63876050 1.29985215
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00494349 0.17274904 0.09810199
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.54164472 0.93812944 0.82963534 0.85929034 0.82213448 0.77709633
#> [7] 0.37104316 0.32990236 0.69971149 0.12949192 0.96605935 0.22871893
#> [13] 0.59280421 0.44048237 0.64261385 0.08655194 0.81462423 0.35063412
#> [19] 0.91691515 0.61789859 0.08655194 0.57569851 0.83710396 0.88097361
#> [25] 0.73105211 0.83710396 0.45013929 0.89547784 0.41118228 0.47851682
#> [31] 0.22871893 0.20142629 0.21520201 0.65922002 0.12949192 0.76186204
#> [37] 0.26474628 0.49681448 0.61789859 0.85929034 0.75417543 0.47851682
#> [43] 0.65922002 0.39148761 0.93812944 0.08655194 0.69167780 0.95910235
#> [49] 0.68358250 0.93106292 0.96605935 0.42104512 0.65093914 0.54164472
#> [55] 0.57569851 0.77709633 0.99317395 0.67545397 0.91691515 0.90976655
#> [61] 0.51486952 0.79962093 0.96605935 0.70772561 0.85189259 0.95211663
#> [67] 0.77709633 0.32990236 0.76186204 0.29776609 0.35063412 0.88824073
#> [73] 0.31920251 0.73105211 0.26474628 0.85929034 0.38131529 0.52389784
#> [79] 0.06065616 0.96605935 0.52389784 0.54164472 0.18733200 0.70772561
#> [85] 0.02648250 0.70772561 0.29776609 0.17294856 0.15834365 0.26474628
#> [91] 0.79962093 0.45013929 0.59280421 0.43078903 0.49681448 0.74646828
#> [97] 0.59280421 0.61789859 0.39148761 0.22871893 0.46903631 0.89547784
#> [103] 0.54164472 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 111 187 123 37 155 133 166 68 6 69 77 136 171
#> 17.45 9.92 13.00 12.52 13.08 14.65 19.98 20.62 15.64 23.23 7.27 21.83 16.57
#> 8 85 129 57 150 93 181 129.1 23 154 56 29 154.1
#> 18.43 16.44 23.41 14.46 20.33 10.33 16.46 23.41 16.92 12.63 12.21 15.45 12.63
#> 88 107 76 51 136.1 194 66 79 69.1 180 197 40 181.1
#> 18.37 11.18 19.22 18.23 21.83 22.40 22.13 16.23 23.23 14.82 21.60 18.00 16.46
#> 37.1 157 51.1 79.1 58 187.1 129.2 125 16 100 145 77.1 97
#> 12.52 15.10 18.23 16.23 19.34 9.92 23.41 15.65 8.71 16.07 10.07 7.27 19.14
#> 5 111.1 23.1 133.1 91 188 93.1 52 134 96 77.2 167 177
#> 16.43 17.45 16.92 14.65 5.33 16.16 10.33 10.42 17.81 14.54 7.27 15.55 12.53
#> 183 133.2 68.1 180.1 139 150.1 49 153 29.1 197.1 37.2 170 117
#> 9.24 14.65 20.62 14.82 21.49 20.33 12.19 21.33 15.45 21.60 12.52 19.54 17.46
#> 164 77.3 117.1 111.2 15 167.1 24 167.2 139.1 113 92 197.2 96.1
#> 23.60 7.27 17.46 17.45 22.68 15.55 23.89 15.55 21.49 22.86 22.92 21.60 14.54
#> 88.1 171.1 179 40.1 18 171.2 181.2 55 136.2 108 107.1 111.3 38
#> 18.37 16.57 18.63 18.00 15.21 16.57 16.46 19.34 21.83 18.29 11.18 17.45 24.00
#> 53 102 47 54 148 98 98.1 161 141 95 28 122 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 44 137 103 162 143 21 118 82 116 144 121 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 27 186 17 95.1 112 172 31 102.1 27.1 82.1 2 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 176 132 151 64 46 27.2 17.1 102.2 67 162.1 64.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 21.1 151.1 132.1 142 198 132.2 186.1 53.1 152 87.1 112.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 198.1 173 95.2 126 64.2 174 102.3 141.2 163 28.1 82.2 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 46.1 104 62 109 38.1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005798075 0.634312454 0.548148788
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.25557808 0.02735844 -0.51289711
#> grade_iii, Cure model
#> 0.98916937
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 140 12.68 1 59 1 0
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 107 11.18 1 54 1 0
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 68 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 6 15.64 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 81 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 159 10.55 1 50 0 1
#> 43 12.10 1 61 0 1
#> 36 21.19 1 48 0 1
#> 60 13.15 1 38 1 0
#> 37 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 14 12.89 1 21 0 0
#> 183.1 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 29.1 15.45 1 68 1 0
#> 50.1 10.02 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 41 18.02 1 40 1 0
#> 192.1 16.44 1 31 1 0
#> 59 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 40 18.00 1 28 1 0
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 110 17.56 1 65 0 1
#> 117 17.46 1 26 0 1
#> 117.1 17.46 1 26 0 1
#> 171 16.57 1 41 0 1
#> 197 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 170 19.54 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 166.1 19.98 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 45 17.42 1 54 0 1
#> 85.1 16.44 1 36 0 0
#> 78.1 23.88 1 43 0 0
#> 91.1 5.33 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 81.2 14.06 1 34 0 0
#> 76 19.22 1 54 0 1
#> 78.2 23.88 1 43 0 0
#> 149 8.37 1 33 1 0
#> 110.1 17.56 1 65 0 1
#> 127 3.53 1 62 0 1
#> 197.1 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 164 23.60 1 76 0 1
#> 194 22.40 1 38 0 1
#> 189 10.51 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 40.1 18.00 1 28 1 0
#> 164.1 23.60 1 76 0 1
#> 194.1 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 169 22.41 1 46 0 0
#> 93 10.33 1 52 0 1
#> 100 16.07 1 60 0 0
#> 108 18.29 1 39 0 1
#> 107.1 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 45.1 17.42 1 54 0 1
#> 51 18.23 1 83 0 1
#> 77.2 7.27 1 67 0 1
#> 52 10.42 1 52 0 1
#> 59.1 10.16 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 29.2 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 61 10.12 1 36 0 1
#> 93.1 10.33 1 52 0 1
#> 90 20.94 1 50 0 1
#> 52.1 10.42 1 52 0 1
#> 81.3 14.06 1 34 0 0
#> 66 22.13 1 53 0 0
#> 158 20.14 1 74 1 0
#> 68.1 20.62 1 44 0 0
#> 91.2 5.33 1 61 0 1
#> 56 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 81.4 14.06 1 34 0 0
#> 4.2 17.64 1 NA 0 1
#> 171.1 16.57 1 41 0 1
#> 133 14.65 1 57 0 0
#> 57 14.46 1 45 0 1
#> 45.2 17.42 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 66.1 22.13 1 53 0 0
#> 197.2 21.60 1 69 1 0
#> 106 16.67 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 57.1 14.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 157.1 15.10 1 47 0 0
#> 159.1 10.55 1 50 0 1
#> 45.3 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 162 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 185 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 33 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 132 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 198 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 162.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 162.2 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 19.1 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 174.1 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 35 24.00 0 51 0 0
#> 186.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 109.1 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 185.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 17 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 2.1 24.00 0 9 0 0
#> 73 24.00 0 NA 0 1
#> 151.1 24.00 0 42 0 0
#> 193.1 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 132.1 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 185.2 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 98.1 24.00 0 34 1 0
#> 82.1 24.00 0 34 0 0
#> 152.1 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 2.2 24.00 0 9 0 0
#> 9.1 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 185.3 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 31.1 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 147.1 24.00 0 76 1 0
#> 137 24.00 0 45 1 0
#> 2.3 24.00 0 9 0 0
#> 141.2 24.00 0 44 1 0
#> 152.2 24.00 0 36 0 1
#> 174.2 24.00 0 49 1 0
#> 94 24.00 0 51 0 1
#> 156 24.00 0 50 1 0
#> 132.2 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.26 NA NA NA
#> 2 age, Cure model 0.0274 NA NA NA
#> 3 grade_ii, Cure model -0.513 NA NA NA
#> 4 grade_iii, Cure model 0.989 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00580 NA NA NA
#> 2 grade_ii, Survival model 0.634 NA NA NA
#> 3 grade_iii, Survival model 0.548 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.25558 0.02736 -0.51290 0.98917
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 235.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.25557808 0.02735844 -0.51289711 0.98916937
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005798075 0.634312454 0.548148788
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91459151 0.77149795 0.01186796 0.54209193 0.81710556 0.54209193
#> [7] 0.68943664 0.23618950 0.78978632 0.60662002 0.41605755 0.69864883
#> [13] 0.96606379 0.83505730 0.80800368 0.20436478 0.74403327 0.78066115
#> [19] 0.61597366 0.76229767 0.91459151 0.09157246 0.74403327 0.61597366
#> [25] 0.69864883 0.38550837 0.54209193 0.58801351 0.39599466 0.04281942
#> [31] 0.20436478 0.42626219 0.44625074 0.44625074 0.52322615 0.17249493
#> [37] 0.27878854 0.94051102 0.31086787 0.27878854 0.94051102 0.47577440
#> [43] 0.54209193 0.01186796 0.96606379 0.69864883 0.32163555 0.01186796
#> [49] 0.93187412 0.42626219 0.99147234 0.17249493 0.89709151 0.05664436
#> [55] 0.12718536 0.39599466 0.05664436 0.12718536 0.64327852 0.11467339
#> [61] 0.87063107 0.59729547 0.35386129 0.81710556 0.34305627 0.47577440
#> [67] 0.36454244 0.94051102 0.85289606 0.90586281 0.61597366 0.57868368
#> [73] 0.88826561 0.87063107 0.22550852 0.85289606 0.69864883 0.14938340
#> [79] 0.26818912 0.23618950 0.96606379 0.79887974 0.07996299 0.69864883
#> [85] 0.52322615 0.66173856 0.67107076 0.47577440 0.36454244 0.46581197
#> [91] 0.14938340 0.17249493 0.51357892 0.09157246 0.33230859 0.67107076
#> [97] 0.25749347 0.64327852 0.83505730 0.47577440 0.29996876 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 183 140 78 85 107 192 13 68 42 6 184 81 91
#> 9.24 12.68 23.88 16.44 11.18 16.44 14.34 20.62 12.43 15.64 17.77 14.06 5.33
#> 159 43 36 60 37 29 14 183.1 15 60.1 29.1 81.1 41
#> 10.55 12.10 21.19 13.15 12.52 15.45 12.89 9.24 22.68 13.15 15.45 14.06 18.02
#> 192.1 188 40 86 36.1 110 117 117.1 171 197 166 77 170
#> 16.44 16.16 18.00 23.81 21.19 17.56 17.46 17.46 16.57 21.60 19.98 7.27 19.54
#> 166.1 77.1 45 85.1 78.1 91.1 81.2 76 78.2 149 110.1 127 197.1
#> 19.98 7.27 17.42 16.44 23.88 5.33 14.06 19.22 23.88 8.37 17.56 3.53 21.60
#> 101 164 194 40.1 164.1 194.1 157 169 93 100 108 107.1 8
#> 9.97 23.60 22.40 18.00 23.60 22.40 15.10 22.41 10.33 16.07 18.29 11.18 18.43
#> 45.1 51 77.2 52 187 29.2 5 61 93.1 90 52.1 81.3 66
#> 17.42 18.23 7.27 10.42 9.92 15.45 16.43 10.12 10.33 20.94 10.42 14.06 22.13
#> 158 68.1 91.2 56 63 81.4 171.1 133 57 45.2 51.1 30 66.1
#> 20.14 20.62 5.33 12.21 22.77 14.06 16.57 14.65 14.46 17.42 18.23 17.43 22.13
#> 197.2 106 15.1 179 57.1 128 157.1 159.1 45.3 105 162 135 185
#> 21.60 16.67 22.68 18.63 14.46 20.35 15.10 10.55 17.42 19.75 24.00 24.00 24.00
#> 103 33 2 132 152 9 182 198 19 162.1 174 162.2 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 19.1 151 174.1 173 118 3 109 22 65 64 35 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 20 163 62 161 193 109.1 72 165 185.1 65.1 54 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 160 82 2.1 151.1 193.1 141 147 196 31 72.1 148 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 185.2 80 200 98.1 82.1 152.1 46 165.1 182.1 121 2.2 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 185.3 31.1 141.1 178 33.1 147.1 137 2.3 141.2 152.2 174.2 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 132.2 38 47 87.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001177047 0.077094735 -0.329504253
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.112700403 0.004185574 -0.027081133
#> grade_iii, Cure model
#> 0.349868750
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 14 12.89 1 21 0 0
#> 8 18.43 1 32 0 0
#> 140 12.68 1 59 1 0
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 6 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 89 11.44 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 40 18.00 1 28 1 0
#> 181 16.46 1 45 0 1
#> 60 13.15 1 38 1 0
#> 8.1 18.43 1 32 0 0
#> 171 16.57 1 41 0 1
#> 4 17.64 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 194 22.40 1 38 0 1
#> 99 21.19 1 38 0 1
#> 155 13.08 1 26 0 0
#> 70 7.38 1 30 1 0
#> 37 12.52 1 57 1 0
#> 127 3.53 1 62 0 1
#> 100 16.07 1 60 0 0
#> 63 22.77 1 31 1 0
#> 85 16.44 1 36 0 0
#> 133.1 14.65 1 57 0 0
#> 114 13.68 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 192 16.44 1 31 1 0
#> 8.2 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 51.1 18.23 1 83 0 1
#> 180 14.82 1 37 0 0
#> 155.2 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 127.1 3.53 1 62 0 1
#> 66 22.13 1 53 0 0
#> 88 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 140.1 12.68 1 59 1 0
#> 99.1 21.19 1 38 0 1
#> 134.1 17.81 1 47 1 0
#> 177 12.53 1 75 0 0
#> 26.1 15.77 1 49 0 1
#> 164 23.60 1 76 0 1
#> 170 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 99.2 21.19 1 38 0 1
#> 42 12.43 1 49 0 1
#> 13 14.34 1 54 0 1
#> 134.2 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 157.1 15.10 1 47 0 0
#> 86 23.81 1 58 0 1
#> 99.3 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 128.1 20.35 1 35 0 1
#> 195 11.76 1 NA 1 0
#> 88.1 18.37 1 47 0 0
#> 129 23.41 1 53 1 0
#> 63.1 22.77 1 31 1 0
#> 171.1 16.57 1 41 0 1
#> 45.1 17.42 1 54 0 1
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 159 10.55 1 50 0 1
#> 123 13.00 1 44 1 0
#> 167 15.55 1 56 1 0
#> 81 14.06 1 34 0 0
#> 140.2 12.68 1 59 1 0
#> 63.2 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 81.1 14.06 1 34 0 0
#> 169 22.41 1 46 0 0
#> 114.1 13.68 1 NA 0 0
#> 169.1 22.41 1 46 0 0
#> 91 5.33 1 61 0 1
#> 25.1 6.32 1 34 1 0
#> 14.1 12.89 1 21 0 0
#> 91.1 5.33 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 40.1 18.00 1 28 1 0
#> 86.1 23.81 1 58 0 1
#> 59.1 10.16 1 NA 1 0
#> 8.3 18.43 1 32 0 0
#> 155.3 13.08 1 26 0 0
#> 117.1 17.46 1 26 0 1
#> 123.1 13.00 1 44 1 0
#> 32 20.90 1 37 1 0
#> 5 16.43 1 51 0 1
#> 10 10.53 1 34 0 0
#> 171.2 16.57 1 41 0 1
#> 86.2 23.81 1 58 0 1
#> 41 18.02 1 40 1 0
#> 189 10.51 1 NA 1 0
#> 169.2 22.41 1 46 0 0
#> 117.2 17.46 1 26 0 1
#> 59.2 10.16 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 110 17.56 1 65 0 1
#> 85.1 16.44 1 36 0 0
#> 69 23.23 1 25 0 1
#> 14.2 12.89 1 21 0 0
#> 40.2 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 51.2 18.23 1 83 0 1
#> 98 24.00 0 34 1 0
#> 3 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 82 24.00 0 34 0 0
#> 74 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 46 24.00 0 71 0 0
#> 82.1 24.00 0 34 0 0
#> 119.1 24.00 0 17 0 0
#> 19 24.00 0 57 0 1
#> 73 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 74.1 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 27 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 3.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 17 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 71 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 83.1 24.00 0 6 0 0
#> 2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 19.1 24.00 0 57 0 1
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 17.1 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 141.1 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 47 24.00 0 38 0 1
#> 7.1 24.00 0 37 1 0
#> 7.2 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 17.2 24.00 0 38 0 1
#> 73.1 24.00 0 NA 0 1
#> 47.1 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 47.2 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 126.1 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 103 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 186 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 122.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 141.2 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 9.1 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 104 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 7.3 24.00 0 37 1 0
#> 17.3 24.00 0 38 0 1
#> 75.2 24.00 0 21 1 0
#> 31 24.00 0 36 0 1
#> 21.2 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 7.4 24.00 0 37 1 0
#> 109.1 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 11.1 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.113 NA NA NA
#> 2 age, Cure model 0.00419 NA NA NA
#> 3 grade_ii, Cure model -0.0271 NA NA NA
#> 4 grade_iii, Cure model 0.350 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00118 NA NA NA
#> 2 grade_ii, Survival model 0.0771 NA NA NA
#> 3 grade_iii, Survival model -0.330 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.112700 0.004186 -0.027081 0.349869
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 256 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.112700403 0.004185574 -0.027081133 0.349868750
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001177047 0.077094735 -0.329504253
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.747865514 0.208732463 0.780193325 0.358828275 0.618335990 0.553767617
#> [7] 0.263345530 0.856320254 0.301844810 0.469285791 0.672491404 0.208732463
#> [13] 0.438422314 0.162398899 0.095202372 0.111788095 0.683420048 0.922302683
#> [19] 0.823442102 0.977629616 0.521671629 0.051249436 0.479883294 0.618335990
#> [25] 0.683420048 0.407906148 0.479883294 0.208732463 0.330362807 0.263345530
#> [31] 0.607494693 0.683420048 0.532350647 0.977629616 0.103474969 0.244615386
#> [37] 0.378440728 0.586021765 0.780193325 0.111788095 0.330362807 0.812511046
#> [43] 0.532350647 0.017751619 0.199186948 0.933394799 0.111788095 0.834371703
#> [49] 0.639877161 0.330362807 0.171492617 0.586021765 0.004006711 0.111788095
#> [55] 0.418054446 0.171492617 0.244615386 0.025804885 0.051249436 0.438422314
#> [61] 0.418054446 0.911204874 0.845347460 0.878117706 0.726178512 0.564591181
#> [67] 0.650800223 0.780193325 0.051249436 0.189783983 0.856320254 0.144244803
#> [73] 0.650800223 0.073027245 0.073027245 0.955427579 0.933394799 0.747865514
#> [79] 0.955427579 0.564591181 0.301844810 0.004006711 0.208732463 0.683420048
#> [85] 0.378440728 0.726178512 0.153330935 0.511007504 0.889129181 0.438422314
#> [91] 0.004006711 0.291979927 0.073027245 0.378440728 0.042507921 0.368590968
#> [97] 0.479883294 0.033842382 0.747865514 0.301844810 0.900146010 0.263345530
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 14 8 140 184 133 6 51 107 40 181 60 8.1 171
#> 12.89 18.43 12.68 17.77 14.65 15.64 18.23 11.18 18.00 16.46 13.15 18.43 16.57
#> 68 194 99 155 70 37 127 100 63 85 133.1 155.1 111
#> 20.62 22.40 21.19 13.08 7.38 12.52 3.53 16.07 22.77 16.44 14.65 13.08 17.45
#> 192 8.2 134 51.1 180 155.2 26 127.1 66 88 117 157 140.1
#> 16.44 18.43 17.81 18.23 14.82 13.08 15.77 3.53 22.13 18.37 17.46 15.10 12.68
#> 99.1 134.1 177 26.1 164 170 25 99.2 42 13 134.2 128 157.1
#> 21.19 17.81 12.53 15.77 23.60 19.54 6.32 21.19 12.43 14.34 17.81 20.35 15.10
#> 86 99.3 45 128.1 88.1 129 63.1 171.1 45.1 101 49 159 123
#> 23.81 21.19 17.42 20.35 18.37 23.41 22.77 16.57 17.42 9.97 12.19 10.55 13.00
#> 167 81 140.2 63.2 150 107.1 90 81.1 169 169.1 91 25.1 14.1
#> 15.55 14.06 12.68 22.77 20.33 11.18 20.94 14.06 22.41 22.41 5.33 6.32 12.89
#> 91.1 167.1 40.1 86.1 8.3 155.3 117.1 123.1 32 5 10 171.2 86.2
#> 5.33 15.55 18.00 23.81 18.43 13.08 17.46 13.00 20.90 16.43 10.53 16.57 23.81
#> 41 169.2 117.2 113 110 85.1 69 14.2 40.2 61 51.2 98 3
#> 18.02 22.41 17.46 22.86 17.56 16.44 23.23 12.89 18.00 10.12 18.23 24.00 24.00
#> 33 144 95 72 82 74 119 46 82.1 119.1 19 126 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 27 161 3.1 152 109 17 53 83 71 118 112 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 21 7 19.1 102 94 17.1 141 62 28 131 172 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 9 174 47 7.1 7.2 122 156 143 21.1 17.2 47.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.2 75 126.1 28.1 103 135 186 191 122.1 11 87 141.2 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 142.1 1 9.1 75.1 104 196 7.3 17.3 75.2 31 21.2 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 7.4 109.1 193 11.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01138224 0.40196683 0.07944912
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.469697022 0.002881779 0.428593400
#> grade_iii, Cure model
#> 1.053736812
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 179 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 16 8.71 1 71 0 1
#> 140 12.68 1 59 1 0
#> 159 10.55 1 50 0 1
#> 113 22.86 1 34 0 0
#> 129 23.41 1 53 1 0
#> 79 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 81 14.06 1 34 0 0
#> 6 15.64 1 39 0 0
#> 107 11.18 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 133 14.65 1 57 0 0
#> 39 15.59 1 37 0 1
#> 61 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 181.1 16.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 169.1 22.41 1 46 0 0
#> 187 9.92 1 39 1 0
#> 37 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 30 17.43 1 78 0 0
#> 39.1 15.59 1 37 0 1
#> 181.2 16.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 86 23.81 1 58 0 1
#> 92 22.92 1 47 0 1
#> 117 17.46 1 26 0 1
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 66 22.13 1 53 0 0
#> 92.1 22.92 1 47 0 1
#> 181.3 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 113.1 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 110 17.56 1 65 0 1
#> 37.1 12.52 1 57 1 0
#> 136 21.83 1 43 0 1
#> 187.1 9.92 1 39 1 0
#> 52 10.42 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 92.2 22.92 1 47 0 1
#> 86.1 23.81 1 58 0 1
#> 63 22.77 1 31 1 0
#> 153 21.33 1 55 1 0
#> 158.1 20.14 1 74 1 0
#> 25.1 6.32 1 34 1 0
#> 184 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 96.1 14.54 1 33 0 1
#> 14 12.89 1 21 0 0
#> 179.1 18.63 1 42 0 0
#> 124.1 9.73 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 168 23.72 1 70 0 0
#> 56 12.21 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 15 22.68 1 48 0 0
#> 111 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 37.2 12.52 1 57 1 0
#> 30.1 17.43 1 78 0 0
#> 50 10.02 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 30.2 17.43 1 78 0 0
#> 110.1 17.56 1 65 0 1
#> 158.2 20.14 1 74 1 0
#> 192 16.44 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 136.1 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 50.1 10.02 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 50.2 10.02 1 NA 1 0
#> 79.2 16.23 1 54 1 0
#> 111.1 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 149.1 8.37 1 33 1 0
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 157 15.10 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 10 10.53 1 34 0 0
#> 91 5.33 1 61 0 1
#> 57.1 14.46 1 45 0 1
#> 69.1 23.23 1 25 0 1
#> 181.4 16.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 124.2 9.73 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 94 24.00 0 51 0 1
#> 152 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 64 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 33 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 104 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 34 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 176 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 191.1 24.00 0 60 0 1
#> 94.1 24.00 0 51 0 1
#> 131 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 19 24.00 0 57 0 1
#> 146 24.00 0 63 1 0
#> 94.2 24.00 0 51 0 1
#> 115 24.00 0 NA 1 0
#> 116 24.00 0 58 0 1
#> 161 24.00 0 45 0 0
#> 53 24.00 0 32 0 1
#> 142.1 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 116.1 24.00 0 58 0 1
#> 35.1 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 151.2 24.00 0 42 0 0
#> 118.2 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 146.1 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 162.2 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 120 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 80 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 165.1 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#> 9.1 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 162.3 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 54.1 24.00 0 53 1 0
#> 186 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 46.1 24.00 0 71 0 0
#> 162.4 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 163.1 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 34.1 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.470 NA NA NA
#> 2 age, Cure model 0.00288 NA NA NA
#> 3 grade_ii, Cure model 0.429 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0114 NA NA NA
#> 2 grade_ii, Survival model 0.402 NA NA NA
#> 3 grade_iii, Survival model 0.0794 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.469697 0.002882 0.428593 1.053737
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.469697022 0.002881779 0.428593400 1.053736812
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01138224 0.40196683 0.07944912
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.230905284 0.240267215 0.415891394 0.259175791 0.915034400 0.709559203
#> [7] 0.803236004 0.041139343 0.010741150 0.496056825 0.196310659 0.187729782
#> [13] 0.656958998 0.531544683 0.789557166 0.196310659 0.593185380 0.543747051
#> [19] 0.858818230 0.125222939 0.957488225 0.082561235 0.155658568 0.683175839
#> [25] 0.415891394 0.063656085 0.063656085 0.887016392 0.722835904 0.631230789
#> [31] 0.163665070 0.371510964 0.543747051 0.415891394 0.298908656 0.000668269
#> [37] 0.027100921 0.339749423 0.605865839 0.288831537 0.075910474 0.027100921
#> [43] 0.415891394 0.125222939 0.041139343 0.196310659 0.319120221 0.722835904
#> [49] 0.089426216 0.887016392 0.830850144 0.496056825 0.027100921 0.000668269
#> [55] 0.051987530 0.110658698 0.163665070 0.957488225 0.308956397 0.929265939
#> [61] 0.605865839 0.696340952 0.240267215 0.196310659 0.003991876 0.775923584
#> [67] 0.010741150 0.057697551 0.350288820 0.844787779 0.278772676 0.722835904
#> [73] 0.371510964 0.003991876 0.140379572 0.140379572 0.371510964 0.319120221
#> [79] 0.163665070 0.472262331 0.110658698 0.089426216 0.762407529 0.568192070
#> [85] 0.484101960 0.496056825 0.350288820 0.268919700 0.404526553 0.929265939
#> [91] 0.103321812 0.670034569 0.580633007 0.018562451 0.817005633 0.985698030
#> [97] 0.631230789 0.018562451 0.415891394 0.872913462 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 97 179 181 8 16 140 159 113 129 79 55 105 81
#> 19.14 18.63 16.46 18.43 8.71 12.68 10.55 22.86 23.41 16.23 19.34 19.75 14.06
#> 6 107 55.1 133 39 61 99 25 175 150 123 181.1 169
#> 15.64 11.18 19.34 14.65 15.59 10.12 21.19 6.32 21.91 20.33 13.00 16.46 22.41
#> 169.1 187 37 57 158 30 39.1 181.2 40 86 92 117 96
#> 22.41 9.92 12.52 14.46 20.14 17.43 15.59 16.46 18.00 23.81 22.92 17.46 14.54
#> 41 66 92.1 181.3 36 113.1 58 110 37.1 136 187.1 52 79.1
#> 18.02 22.13 22.92 16.46 21.19 22.86 19.34 17.56 12.52 21.83 9.92 10.42 16.23
#> 92.2 86.1 63 153 158.1 25.1 184 149 96.1 14 179.1 58.1 168
#> 22.92 23.81 22.77 21.33 20.14 6.32 17.77 8.37 14.54 12.89 18.63 19.34 23.72
#> 56 129.1 15 111 93 51 37.2 30.1 168.1 190 190.1 30.2 110.1
#> 12.21 23.41 22.68 17.45 10.33 18.23 12.52 17.43 23.72 20.81 20.81 17.43 17.56
#> 158.2 192 153.1 136.1 42 29 5 79.2 111.1 108 106 149.1 139
#> 20.14 16.44 21.33 21.83 12.43 15.45 16.43 16.23 17.45 18.29 16.67 8.37 21.49
#> 155 157 69 10 91 57.1 69.1 181.4 101 94 152 27 44
#> 13.08 15.10 23.23 10.53 5.33 14.46 23.23 16.46 9.97 24.00 24.00 24.00 24.00
#> 118 173 64 173.1 142 82 33 28 104 182 34 72 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 138 141 200 176 38 27.1 178 11 191 193 35 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 21 191.1 94.1 131 62 33.1 67 19 146 94.2 116 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 142.1 102 172 148 116.1 35.1 118.1 151.1 9 119 162 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 28.1 22 146.1 162.1 174 162.2 165 135 120 200.1 80 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 165.1 152.1 9.1 174.1 162.3 54 20 54.1 186 144 46.1 162.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 163.1 141.1 74 34.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003315966 0.674855928 0.619905420
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.527476872 0.003537455 0.387437561
#> grade_iii, Cure model
#> 1.115464956
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 130 16.47 1 53 0 1
#> 154 12.63 1 20 1 0
#> 129 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 153 21.33 1 55 1 0
#> 77 7.27 1 67 0 1
#> 69 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 125 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 189 10.51 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 88 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 32 20.90 1 37 1 0
#> 61 10.12 1 36 0 1
#> 197 21.60 1 69 1 0
#> 40 18.00 1 28 1 0
#> 26 15.77 1 49 0 1
#> 184 17.77 1 38 0 0
#> 155 13.08 1 26 0 0
#> 192 16.44 1 31 1 0
#> 86 23.81 1 58 0 1
#> 106 16.67 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 58 19.34 1 39 0 0
#> 49 12.19 1 48 1 0
#> 124 9.73 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 76.1 19.22 1 54 0 1
#> 127 3.53 1 62 0 1
#> 99 21.19 1 38 0 1
#> 76.2 19.22 1 54 0 1
#> 40.1 18.00 1 28 1 0
#> 59 10.16 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 153.1 21.33 1 55 1 0
#> 96.1 14.54 1 33 0 1
#> 26.1 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 69.2 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 78 23.88 1 43 0 0
#> 25 6.32 1 34 1 0
#> 108 18.29 1 39 0 1
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 30 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 114.1 13.68 1 NA 0 0
#> 108.1 18.29 1 39 0 1
#> 5 16.43 1 51 0 1
#> 66 22.13 1 53 0 0
#> 55 19.34 1 69 0 1
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 26.2 15.77 1 49 0 1
#> 59.1 10.16 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 55.1 19.34 1 69 0 1
#> 96.2 14.54 1 33 0 1
#> 158 20.14 1 74 1 0
#> 170 19.54 1 43 0 1
#> 76.3 19.22 1 54 0 1
#> 127.1 3.53 1 62 0 1
#> 111 17.45 1 47 0 1
#> 97 19.14 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 63 22.77 1 31 1 0
#> 157 15.10 1 47 0 0
#> 105 19.75 1 60 0 0
#> 36.2 21.19 1 48 0 1
#> 58.1 19.34 1 39 0 0
#> 153.2 21.33 1 55 1 0
#> 153.3 21.33 1 55 1 0
#> 99.1 21.19 1 38 0 1
#> 25.1 6.32 1 34 1 0
#> 55.2 19.34 1 69 0 1
#> 108.2 18.29 1 39 0 1
#> 68 20.62 1 44 0 0
#> 61.1 10.12 1 36 0 1
#> 36.3 21.19 1 48 0 1
#> 24 23.89 1 38 0 0
#> 114.2 13.68 1 NA 0 0
#> 29.1 15.45 1 68 1 0
#> 190 20.81 1 42 1 0
#> 128 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 55.3 19.34 1 69 0 1
#> 175.1 21.91 1 43 0 0
#> 60 13.15 1 38 1 0
#> 167 15.55 1 56 1 0
#> 106.1 16.67 1 49 1 0
#> 5.1 16.43 1 51 0 1
#> 168.1 23.72 1 70 0 0
#> 63.1 22.77 1 31 1 0
#> 189.1 10.51 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 43 12.10 1 61 0 1
#> 51 18.23 1 83 0 1
#> 106.2 16.67 1 49 1 0
#> 90 20.94 1 50 0 1
#> 181 16.46 1 45 0 1
#> 181.1 16.46 1 45 0 1
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 2 24.00 0 9 0 0
#> 47.1 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 115 24.00 0 NA 1 0
#> 48 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 31 24.00 0 36 0 1
#> 148.1 24.00 0 61 1 0
#> 27.1 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 33.1 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 19.2 24.00 0 57 0 1
#> 143 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 71 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 19.3 24.00 0 57 0 1
#> 84 24.00 0 39 0 1
#> 31.1 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 19.4 24.00 0 57 0 1
#> 152 24.00 0 36 0 1
#> 160.1 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 22.1 24.00 0 52 1 0
#> 87.1 24.00 0 27 0 0
#> 12.1 24.00 0 63 0 0
#> 118 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 28.1 24.00 0 67 1 0
#> 146 24.00 0 63 1 0
#> 121 24.00 0 57 1 0
#> 176.1 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 122.1 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 147.1 24.00 0 76 1 0
#> 31.2 24.00 0 36 0 1
#> 87.2 24.00 0 27 0 0
#> 118.1 24.00 0 44 1 0
#> 22.2 24.00 0 52 1 0
#> 132.1 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 165.1 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 3.1 24.00 0 31 1 0
#> 122.2 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.527 NA NA NA
#> 2 age, Cure model 0.00354 NA NA NA
#> 3 grade_ii, Cure model 0.387 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00332 NA NA NA
#> 2 grade_ii, Survival model 0.675 NA NA NA
#> 3 grade_iii, Survival model 0.620 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.527477 0.003537 0.387438 1.115465
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.527476872 0.003537455 0.387437561 1.115464956
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003315966 0.674855928 0.619905420
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.77778492 0.92494957 0.21640813 0.90911147 0.64763407 0.42381165
#> [7] 0.97580749 0.24068839 0.46729836 0.84347416 0.32326008 0.24068839
#> [13] 0.93537417 0.68388061 0.86590408 0.88239817 0.53173647 0.95082246
#> [19] 0.39775866 0.71883121 0.82629496 0.73227439 0.91968452 0.79640043
#> [25] 0.13081175 0.75885838 0.46729836 0.60218927 0.94056009 0.87690509
#> [31] 0.64763407 0.99042336 0.46729836 0.64763407 0.71883121 0.89845508
#> [37] 0.96090349 0.73901877 0.42381165 0.88239817 0.82629496 0.85484036
#> [43] 0.24068839 0.97085558 0.08448795 0.98072642 0.69112987 0.36893486
#> [49] 0.56775625 0.75227956 0.82038150 0.69112987 0.80849776 0.35404868
#> [55] 0.60218927 0.16304083 0.90380248 0.96090349 0.82629496 0.33904137
#> [61] 0.60218927 0.88239817 0.57656213 0.59374913 0.64763407 0.99042336
#> [67] 0.74568372 0.67661837 0.39775866 0.29222485 0.87140751 0.58516952
#> [73] 0.46729836 0.60218927 0.42381165 0.42381165 0.46729836 0.98072642
#> [79] 0.60218927 0.69112987 0.54994292 0.95082246 0.46729836 0.03498782
#> [85] 0.85484036 0.54093598 0.55892675 0.93018191 0.60218927 0.36893486
#> [91] 0.91441675 0.84918321 0.75885838 0.80849776 0.16304083 0.29222485
#> [97] 0.79640043 0.94570903 0.71192811 0.75885838 0.52233860 0.78408302
#> [103] 0.78408302 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 130 154 129 81 76 153 77 69 36 125 169 69.1 56
#> 16.47 12.63 23.41 14.06 19.22 21.33 7.27 23.23 21.19 15.65 22.41 23.23 12.21
#> 88 18 96 32 61 197 40 26 184 155 192 86 106
#> 18.37 15.21 14.54 20.90 10.12 21.60 18.00 15.77 17.77 13.08 16.44 23.81 16.67
#> 36.1 58 49 180 76.1 127 99 76.2 40.1 57 187 110 153.1
#> 21.19 19.34 12.19 14.82 19.22 3.53 21.19 19.22 18.00 14.46 9.92 17.56 21.33
#> 96.1 26.1 29 69.2 183 78 25 108 175 150 30 188 108.1
#> 14.54 15.77 15.45 23.23 9.24 23.88 6.32 18.29 21.91 20.33 17.43 16.16 18.29
#> 5 66 55 168 13 187.1 26.2 194 55.1 96.2 158 170 76.3
#> 16.43 22.13 19.34 23.72 14.34 9.92 15.77 22.40 19.34 14.54 20.14 19.54 19.22
#> 127.1 111 97 197.1 63 157 105 36.2 58.1 153.2 153.3 99.1 25.1
#> 3.53 17.45 19.14 21.60 22.77 15.10 19.75 21.19 19.34 21.33 21.33 21.19 6.32
#> 55.2 108.2 68 61.1 36.3 24 29.1 190 128 37 55.3 175.1 60
#> 19.34 18.29 20.62 10.12 21.19 23.89 15.45 20.81 20.35 12.52 19.34 21.91 13.15
#> 167 106.1 5.1 168.1 63.1 192.1 43 51 106.2 90 181 181.1 44
#> 15.55 16.67 16.43 23.72 22.77 16.44 12.10 18.23 16.67 20.94 16.46 16.46 24.00
#> 47 27 193 186 135 173 148 2 47.1 1 182 138 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 173.1 35 102 31 148.1 27.1 178 160 33 198 46 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 9 19.1 38 87 33.1 22 95 2.1 19.2 143 191 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 176 19.3 84 31.1 65 19.4 152 160.1 132 20 131 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 22.1 87.1 12.1 118 28 28.1 146 121 176.1 162 122 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 147 165 122.1 74.1 147.1 31.2 87.2 118.1 22.2 132.1 80 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 21.1 3.1 122.2 131.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003009805 1.120761380 0.570913427
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.244399269 0.003421401 0.019053681
#> grade_iii, Cure model
#> 0.615995979
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 194 22.40 1 38 0 1
#> 37 12.52 1 57 1 0
#> 192 16.44 1 31 1 0
#> 86 23.81 1 58 0 1
#> 4 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 36 21.19 1 48 0 1
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 4.1 17.64 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 111 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 158 20.14 1 74 1 0
#> 43 12.10 1 61 0 1
#> 166 19.98 1 48 0 0
#> 123 13.00 1 44 1 0
#> 66 22.13 1 53 0 0
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 5 16.43 1 51 0 1
#> 187 9.92 1 39 1 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 6 15.64 1 39 0 0
#> 113 22.86 1 34 0 0
#> 51 18.23 1 83 0 1
#> 32 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 167 15.55 1 56 1 0
#> 127.1 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 180 14.82 1 37 0 0
#> 41 18.02 1 40 1 0
#> 40 18.00 1 28 1 0
#> 168.1 23.72 1 70 0 0
#> 89 11.44 1 NA 0 0
#> 175.1 21.91 1 43 0 0
#> 25 6.32 1 34 1 0
#> 63 22.77 1 31 1 0
#> 89.1 11.44 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 130 16.47 1 53 0 1
#> 29 15.45 1 68 1 0
#> 124 9.73 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 86.1 23.81 1 58 0 1
#> 189 10.51 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 157 15.10 1 47 0 0
#> 187.2 9.92 1 39 1 0
#> 101 9.97 1 10 0 1
#> 114.2 13.68 1 NA 0 0
#> 50 10.02 1 NA 1 0
#> 4.2 17.64 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 123.1 13.00 1 44 1 0
#> 99 21.19 1 38 0 1
#> 61 10.12 1 36 0 1
#> 169.1 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 41.1 18.02 1 40 1 0
#> 128 20.35 1 35 0 1
#> 41.2 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 5.1 16.43 1 51 0 1
#> 40.1 18.00 1 28 1 0
#> 114.3 13.68 1 NA 0 0
#> 37.1 12.52 1 57 1 0
#> 58.1 19.34 1 39 0 0
#> 25.1 6.32 1 34 1 0
#> 8 18.43 1 32 0 0
#> 139 21.49 1 63 1 0
#> 158.1 20.14 1 74 1 0
#> 66.1 22.13 1 53 0 0
#> 51.1 18.23 1 83 0 1
#> 57 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 29.1 15.45 1 68 1 0
#> 179.1 18.63 1 42 0 0
#> 180.1 14.82 1 37 0 0
#> 5.2 16.43 1 51 0 1
#> 58.2 19.34 1 39 0 0
#> 110 17.56 1 65 0 1
#> 79 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 99.1 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 175.2 21.91 1 43 0 0
#> 4.3 17.64 1 NA 0 1
#> 43.1 12.10 1 61 0 1
#> 26 15.77 1 49 0 1
#> 60 13.15 1 38 1 0
#> 159.1 10.55 1 50 0 1
#> 97 19.14 1 65 0 1
#> 192.1 16.44 1 31 1 0
#> 175.3 21.91 1 43 0 0
#> 179.2 18.63 1 42 0 0
#> 157.1 15.10 1 47 0 0
#> 171 16.57 1 41 0 1
#> 108 18.29 1 39 0 1
#> 140 12.68 1 59 1 0
#> 78.1 23.88 1 43 0 0
#> 128.1 20.35 1 35 0 1
#> 177.1 12.53 1 75 0 0
#> 36.1 21.19 1 48 0 1
#> 141 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 165.1 24.00 0 47 0 0
#> 116.1 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 54.1 24.00 0 53 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 143 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 54.2 24.00 0 53 1 0
#> 119 24.00 0 17 0 0
#> 185 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 173.1 24.00 0 19 0 1
#> 44.1 24.00 0 56 0 0
#> 174.1 24.00 0 49 1 0
#> 94.1 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 143.1 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 176 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 141.2 24.00 0 44 1 0
#> 165.2 24.00 0 47 0 0
#> 142.2 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 200 24.00 0 64 0 0
#> 33.1 24.00 0 53 0 0
#> 119.1 24.00 0 17 0 0
#> 98.1 24.00 0 34 1 0
#> 65.1 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 20 24.00 0 46 1 0
#> 22.1 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 116.2 24.00 0 58 0 1
#> 19.1 24.00 0 57 0 1
#> 12.1 24.00 0 63 0 0
#> 82.1 24.00 0 34 0 0
#> 196 24.00 0 19 0 0
#> 135.1 24.00 0 58 1 0
#> 82.2 24.00 0 34 0 0
#> 142.3 24.00 0 53 0 0
#> 33.2 24.00 0 53 0 0
#> 44.2 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 31 24.00 0 36 0 1
#> 116.3 24.00 0 58 0 1
#> 191 24.00 0 60 0 1
#> 38 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 118.1 24.00 0 44 1 0
#> 19.2 24.00 0 57 0 1
#> 94.2 24.00 0 51 0 1
#> 191.1 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.244 NA NA NA
#> 2 age, Cure model 0.00342 NA NA NA
#> 3 grade_ii, Cure model 0.0191 NA NA NA
#> 4 grade_iii, Cure model 0.616 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00301 NA NA NA
#> 2 grade_ii, Survival model 1.12 NA NA NA
#> 3 grade_iii, Survival model 0.571 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.244399 0.003421 0.019054 0.615996
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 253.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.244399269 0.003421401 0.019053681 0.615995979
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003009805 1.120761380 0.570913427
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.99061398 0.34660833 0.92030953 0.77074840 0.16315215 0.90954755
#> [7] 0.45716212 0.87595353 0.10480233 0.39002521 0.20513822 0.57355651
#> [13] 0.88172363 0.74943156 0.58289634 0.54517733 0.93597776 0.56405982
#> [19] 0.89316577 0.36141472 0.66264993 0.78417866 0.96659260 0.62745287
#> [25] 0.93074908 0.31638537 0.94627664 0.82274352 0.28273048 0.68026033
#> [31] 0.50220053 0.04295489 0.82897629 0.99061398 0.26467060 0.85847804
#> [37] 0.69709663 0.72015597 0.20513822 0.39002521 0.98112610 0.30066733
#> [43] 0.76371227 0.83508819 0.04295489 0.16315215 0.96659260 0.84679538
#> [49] 0.96659260 0.96153648 0.51323766 0.89316577 0.45716212 0.95645835
#> [55] 0.31638537 0.81650486 0.69709663 0.52424130 0.69709663 0.74218538
#> [61] 0.78417866 0.72015597 0.92030953 0.58289634 0.98112610 0.65376951
#> [67] 0.44410574 0.54517733 0.36141472 0.68026033 0.87014199 0.83508819
#> [73] 0.62745287 0.85847804 0.78417866 0.58289634 0.73487396 0.80370637
#> [79] 0.58289634 0.45716212 0.24523410 0.39002521 0.93597776 0.81013218
#> [85] 0.88748967 0.94627664 0.61850382 0.77074840 0.39002521 0.62745287
#> [91] 0.84679538 0.75660569 0.67151230 0.90413427 0.10480233 0.52424130
#> [97] 0.90954755 0.45716212 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 127 194 37 192 86 177 36 13 78 175 168 170 81
#> 3.53 22.40 12.52 16.44 23.81 12.53 21.19 14.34 23.88 21.91 23.72 19.54 14.06
#> 111 58 158 43 166 123 66 88 5 187 179 56 169
#> 17.45 19.34 20.14 12.10 19.98 13.00 22.13 18.37 16.43 9.92 18.63 12.21 22.41
#> 159 6 113 51 32 24 167 127.1 92 180 41 40 168.1
#> 10.55 15.64 22.86 18.23 20.90 23.89 15.55 3.53 22.92 14.82 18.02 18.00 23.72
#> 175.1 25 63 130 29 24.1 86.1 187.1 157 187.2 101 68 123.1
#> 21.91 6.32 22.77 16.47 15.45 23.89 23.81 9.92 15.10 9.92 9.97 20.62 13.00
#> 99 61 169.1 125 41.1 128 41.2 117 5.1 40.1 37.1 58.1 25.1
#> 21.19 10.12 22.41 15.65 18.02 20.35 18.02 17.46 16.43 18.00 12.52 19.34 6.32
#> 8 139 158.1 66.1 51.1 57 29.1 179.1 180.1 5.2 58.2 110 79
#> 18.43 21.49 20.14 22.13 18.23 14.46 15.45 18.63 14.82 16.43 19.34 17.56 16.23
#> 55 99.1 69 175.2 43.1 26 60 159.1 97 192.1 175.3 179.2 157.1
#> 19.34 21.19 23.23 21.91 12.10 15.77 13.15 10.55 19.14 16.44 21.91 18.63 15.10
#> 171 108 140 78.1 128.1 177.1 36.1 141 44 144 54 135 142
#> 16.57 18.29 12.68 23.88 20.35 12.53 21.19 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 178 21 165 174 116 65 141.1 83 151 11 19 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 3 1 165.1 116.1 12 54.1 46 95 22 102 143 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.2 119 185 35 9 74 173.1 44.1 174.1 94.1 172 143.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 33 82 176 142.1 141.2 165.2 142.2 193 200 33.1 119.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 46.1 20 22.1 71 119.2 116.2 19.1 12.1 82.1 196 135.1 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.3 33.2 44.2 112 31 116.3 191 38 122 137 161 118.1 19.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 191.1 121 186
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01389313 0.48390272 0.46656524
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.47779552 0.01880028 0.76252145
#> grade_iii, Cure model
#> 1.57070062
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 188 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 187 9.92 1 39 1 0
#> 197 21.60 1 69 1 0
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 96 14.54 1 33 0 1
#> 124 9.73 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 183 9.24 1 67 1 0
#> 158 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 117.1 17.46 1 26 0 1
#> 105 19.75 1 60 0 0
#> 96.1 14.54 1 33 0 1
#> 96.2 14.54 1 33 0 1
#> 26 15.77 1 49 0 1
#> 175.1 21.91 1 43 0 0
#> 37 12.52 1 57 1 0
#> 26.1 15.77 1 49 0 1
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 106 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 117.2 17.46 1 26 0 1
#> 171.1 16.57 1 41 0 1
#> 61 10.12 1 36 0 1
#> 25 6.32 1 34 1 0
#> 134.1 17.81 1 47 1 0
#> 106.1 16.67 1 49 1 0
#> 42 12.43 1 49 0 1
#> 36 21.19 1 48 0 1
#> 190 20.81 1 42 1 0
#> 159 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 149 8.37 1 33 1 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 159.1 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 16 8.71 1 71 0 1
#> 166 19.98 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 41 18.02 1 40 1 0
#> 18 15.21 1 49 1 0
#> 92.1 22.92 1 47 0 1
#> 190.1 20.81 1 42 1 0
#> 157.1 15.10 1 47 0 0
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 124.1 9.73 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 86 23.81 1 58 0 1
#> 194 22.40 1 38 0 1
#> 197.1 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 124.2 9.73 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 10.1 10.53 1 34 0 0
#> 100 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 14 12.89 1 21 0 0
#> 93 10.33 1 52 0 1
#> 153 21.33 1 55 1 0
#> 29 15.45 1 68 1 0
#> 50 10.02 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 57 14.46 1 45 0 1
#> 77.1 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 69.1 23.23 1 25 0 1
#> 26.2 15.77 1 49 0 1
#> 183.2 9.24 1 67 1 0
#> 183.3 9.24 1 67 1 0
#> 106.2 16.67 1 49 1 0
#> 183.4 9.24 1 67 1 0
#> 179 18.63 1 42 0 0
#> 167 15.55 1 56 1 0
#> 29.1 15.45 1 68 1 0
#> 45 17.42 1 54 0 1
#> 91.1 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 24.1 23.89 1 38 0 0
#> 145 10.07 1 65 1 0
#> 77.2 7.27 1 67 0 1
#> 123.1 13.00 1 44 1 0
#> 26.3 15.77 1 49 0 1
#> 100.1 16.07 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 136.1 21.83 1 43 0 1
#> 96.3 14.54 1 33 0 1
#> 197.2 21.60 1 69 1 0
#> 170.1 19.54 1 43 0 1
#> 179.1 18.63 1 42 0 0
#> 91.2 5.33 1 61 0 1
#> 191 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 47 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 3 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 47.1 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 172 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 62 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 121.1 24.00 0 57 1 0
#> 173.1 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 98.1 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 162 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 12.1 24.00 0 63 0 0
#> 3.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 12.2 24.00 0 63 0 0
#> 9 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 146 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 122.1 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 64.1 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 118 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 144 24.00 0 28 0 1
#> 98.2 24.00 0 34 1 0
#> 176.1 24.00 0 43 0 1
#> 21.2 24.00 0 47 0 0
#> 47.2 24.00 0 38 0 1
#> 72.1 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 162.1 24.00 0 51 0 0
#> 64.2 24.00 0 43 0 0
#> 48 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 34.2 24.00 0 36 0 0
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 142.1 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 83 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 3.2 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 156.1 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 80.1 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 143.1 24.00 0 51 0 0
#> 47.3 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.48 NA NA NA
#> 2 age, Cure model 0.0188 NA NA NA
#> 3 grade_ii, Cure model 0.763 NA NA NA
#> 4 grade_iii, Cure model 1.57 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0139 NA NA NA
#> 2 grade_ii, Survival model 0.484 NA NA NA
#> 3 grade_iii, Survival model 0.467 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.4778 0.0188 0.7625 1.5707
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.47779552 0.01880028 0.76252145 1.57070062
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01389313 0.48390272 0.46656524
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7624385 0.9774377 0.4678329 0.6345409 0.5396635 0.6912144 0.9044281
#> [8] 0.9464008 0.4961374 0.4358592 0.7568985 0.3607066 0.8454570 0.6191366
#> [15] 0.9500677 0.5943283 0.1267019 0.6912144 0.6109993 0.8454570 0.8454570
#> [22] 0.7837000 0.4358592 0.8963615 0.7837000 0.6709899 0.8272896 0.7226599
#> [29] 0.7399892 0.8881255 0.6845796 0.6912144 0.7399892 0.9315206 0.9872412
#> [36] 0.6709899 0.7226599 0.9004143 0.5396635 0.5677448 0.9083941 0.9427082
#> [43] 0.9706555 0.3103144 0.7512662 0.8922610 0.8364329 0.9083941 0.9161603
#> [50] 0.9672370 0.6027185 0.5396635 0.2285275 0.7102297 0.8364329 0.6638527
#> [57] 0.8226580 0.3607066 0.5677448 0.8272896 0.8034934 0.8756592 0.7624385
#> [64] 0.2769007 0.4185083 0.4961374 0.6565724 0.3998394 0.9161603 0.7731644
#> [71] 0.9740552 0.9905025 0.8839679 0.9277217 0.5290249 0.8133050 0.9500677
#> [78] 0.8628470 0.9774377 0.5854974 0.8714145 0.3103144 0.7837000 0.9500677
#> [85] 0.9500677 0.7226599 0.9500677 0.6420026 0.8084369 0.8133050 0.7165088
#> [92] 0.9905025 0.9238870 0.9315206 0.1267019 0.9390037 0.9774377 0.8756592
#> [99] 0.7837000 0.7731644 0.8628470 0.4678329 0.8454570 0.4961374 0.6191366
#> [106] 0.6420026 0.9905025 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 188 77 136 55 99 117 43 187 197 175 5 92 96
#> 16.16 7.27 21.83 19.34 21.19 17.46 12.10 9.92 21.60 21.91 16.43 22.92 14.54
#> 170 183 158 24 117.1 105 96.1 96.2 26 175.1 37 26.1 134
#> 19.54 9.24 20.14 23.89 17.46 19.75 14.54 14.54 15.77 21.91 12.52 15.77 17.81
#> 157 106 171 154 110 117.2 171.1 61 25 134.1 106.1 42 36
#> 15.10 16.67 16.57 12.63 17.56 17.46 16.57 10.12 6.32 17.81 16.67 12.43 21.19
#> 190 159 101 149 69 85 177 133 159.1 10 16 166 36.1
#> 20.81 10.55 9.97 8.37 23.23 16.44 12.53 14.65 10.55 10.53 8.71 19.98 21.19
#> 78 111 133.1 41 18 92.1 190.1 157.1 39 123 188.1 86 194
#> 23.88 17.45 14.65 18.02 15.21 22.92 20.81 15.10 15.59 13.00 16.16 23.81 22.40
#> 197.1 8 63 10.1 100 70 91 14 93 153 29 183.1 57
#> 21.60 18.43 22.77 10.53 16.07 7.38 5.33 12.89 10.33 21.33 15.45 9.24 14.46
#> 77.1 68 13 69.1 26.2 183.2 183.3 106.2 183.4 179 167 29.1 45
#> 7.27 20.62 14.34 23.23 15.77 9.24 9.24 16.67 9.24 18.63 15.55 15.45 17.42
#> 91.1 52 61.1 24.1 145 77.2 123.1 26.3 100.1 57.1 136.1 96.3 197.2
#> 5.33 10.42 10.12 23.89 10.07 7.27 13.00 15.77 16.07 14.46 21.83 14.54 21.60
#> 170.1 179.1 91.2 191 198 173 72 47 64 12 3 178 98
#> 19.54 18.63 5.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 34 47.1 172 121 82 62 11 121.1 173.1 182 84 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 38 53 98.1 132 162 121.2 34.1 156 12.1 3.1 65 12.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 62.1 176 19 146 21 122 116 122.1 143 21.1 64.1 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 142 144 98.2 176.1 21.2 47.2 72.1 80 162.1 64.2 48 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 20 22 33 138 116.1 142.1 135 83 104 112 3.2 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 156.1 165 71.1 102 94 80.1 137 103 161 143.1 47.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002302825 0.856837360 0.273205982
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05040308 0.01692035 0.57517999
#> grade_iii, Cure model
#> 0.80340321
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 180 14.82 1 37 0 0
#> 60 13.15 1 38 1 0
#> 129 23.41 1 53 1 0
#> 92 22.92 1 47 0 1
#> 168 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 96 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 177 12.53 1 75 0 0
#> 88 18.37 1 47 0 0
#> 159 10.55 1 50 0 1
#> 169 22.41 1 46 0 0
#> 123 13.00 1 44 1 0
#> 114 13.68 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 171 16.57 1 41 0 1
#> 190 20.81 1 42 1 0
#> 66.1 22.13 1 53 0 0
#> 52 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 40 18.00 1 28 1 0
#> 133 14.65 1 57 0 0
#> 158 20.14 1 74 1 0
#> 113 22.86 1 34 0 0
#> 81 14.06 1 34 0 0
#> 57 14.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 45 17.42 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 88.1 18.37 1 47 0 0
#> 69 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 16 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 108.1 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 70 7.38 1 30 1 0
#> 58.1 19.34 1 39 0 0
#> 15 22.68 1 48 0 0
#> 10 10.53 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 90 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 86 23.81 1 58 0 1
#> 55 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 149 8.37 1 33 1 0
#> 13 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 166 19.98 1 48 0 0
#> 140 12.68 1 59 1 0
#> 86.1 23.81 1 58 0 1
#> 60.1 13.15 1 38 1 0
#> 88.2 18.37 1 47 0 0
#> 90.1 20.94 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 169.1 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 90.2 20.94 1 50 0 1
#> 130 16.47 1 53 0 1
#> 56.1 12.21 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 79.1 16.23 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 36 21.19 1 48 0 1
#> 18 15.21 1 49 1 0
#> 51 18.23 1 83 0 1
#> 26 15.77 1 49 0 1
#> 154.1 12.63 1 20 1 0
#> 49 12.19 1 48 1 0
#> 26.1 15.77 1 49 0 1
#> 136 21.83 1 43 0 1
#> 157 15.10 1 47 0 0
#> 92.1 22.92 1 47 0 1
#> 90.3 20.94 1 50 0 1
#> 60.2 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 197.1 21.60 1 69 1 0
#> 187.1 9.92 1 39 1 0
#> 36.1 21.19 1 48 0 1
#> 81.1 14.06 1 34 0 0
#> 32 20.90 1 37 1 0
#> 37.2 12.52 1 57 1 0
#> 25 6.32 1 34 1 0
#> 25.1 6.32 1 34 1 0
#> 128 20.35 1 35 0 1
#> 167 15.55 1 56 1 0
#> 57.2 14.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 189.1 10.51 1 NA 1 0
#> 190.1 20.81 1 42 1 0
#> 136.1 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 190.2 20.81 1 42 1 0
#> 110.1 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 55.1 19.34 1 69 0 1
#> 169.2 22.41 1 46 0 0
#> 20 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 20.1 24.00 0 46 1 0
#> 152.1 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 104.1 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 72.2 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 178 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 20.2 24.00 0 46 1 0
#> 71 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 103 24.00 0 56 1 0
#> 138.1 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 126.2 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 7 24.00 0 37 1 0
#> 142.1 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 2.1 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 112 24.00 0 61 0 0
#> 65.1 24.00 0 57 1 0
#> 163.1 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 118.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 176.1 24.00 0 43 0 1
#> 176.2 24.00 0 43 0 1
#> 126.3 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 104.2 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 182.1 24.00 0 35 0 0
#> 151.1 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 174.1 24.00 0 49 1 0
#> 152.2 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 72.3 24.00 0 40 0 1
#> 143.2 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 126.4 24.00 0 48 0 0
#> 7.1 24.00 0 37 1 0
#> 172 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 200 24.00 0 64 0 0
#> 2.2 24.00 0 9 0 0
#> 75.1 24.00 0 21 1 0
#> 165.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.05 NA NA NA
#> 2 age, Cure model 0.0169 NA NA NA
#> 3 grade_ii, Cure model 0.575 NA NA NA
#> 4 grade_iii, Cure model 0.803 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00230 NA NA NA
#> 2 grade_ii, Survival model 0.857 NA NA NA
#> 3 grade_iii, Survival model 0.273 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05040 0.01692 0.57518 0.80340
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 259.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05040308 0.01692035 0.57517999 0.80340321
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002302825 0.856837360 0.273205982
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.03038066 0.01019968 0.72579528 0.79480824 0.10448142 0.15444137
#> [7] 0.08544857 0.23873542 0.44151460 0.93487682 0.74128366 0.83863605
#> [13] 0.85271194 0.48733622 0.91454536 0.20300000 0.81690212 0.90775936
#> [19] 0.61272217 0.38480555 0.23873542 0.92810388 0.56122142 0.55223051
#> [25] 0.73353444 0.42270197 0.17818932 0.77951521 0.74901525 0.74901525
#> [31] 0.65463615 0.67065255 0.59560999 0.56122142 0.48733622 0.13002921
#> [37] 0.88030824 0.51513720 0.96134833 0.63806242 0.94159967 0.57844928
#> [43] 0.51513720 0.60423297 0.97442023 0.44151460 0.19055227 0.92132274
#> [49] 0.10448142 0.33235430 0.64635824 0.05259774 0.44151460 0.28781213
#> [55] 0.96791039 0.77184222 0.95478108 0.43209757 0.82425861 0.05259774
#> [61] 0.79480824 0.48733622 0.33235430 0.85978847 0.20300000 0.98087836
#> [67] 0.69460917 0.13002921 0.33235430 0.62118841 0.88030824 0.85978847
#> [73] 0.65463615 0.47794340 0.31022402 0.71033897 0.53370639 0.67869156
#> [79] 0.83863605 0.89406949 0.67869156 0.26349018 0.71806286 0.15444137
#> [85] 0.33235430 0.79480824 0.62963586 0.28781213 0.94159967 0.31022402
#> [91] 0.77951521 0.37422678 0.85978847 0.98733112 0.98733112 0.41309573
#> [97] 0.70252121 0.74901525 0.90091812 0.38480555 0.26349018 0.54305914
#> [103] 0.38480555 0.57844928 0.82425861 0.44151460 0.20300000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 78 24 180 60 129 92 168 66 58 145 96 154 177
#> 23.88 23.89 14.82 13.15 23.41 22.92 23.72 22.13 19.34 10.07 14.54 12.63 12.53
#> 88 159 169 123 107 171 190 66.1 52 134 40 133 158
#> 18.37 10.55 22.41 13.00 11.18 16.57 20.81 22.13 10.42 17.81 18.00 14.65 20.14
#> 113 81 57 57.1 79 188 45 134.1 88.1 69 56 108 16
#> 22.86 14.06 14.46 14.46 16.23 16.16 17.42 17.81 18.37 23.23 12.21 18.29 8.71
#> 192 187 110 108.1 106 70 58.1 15 10 129.1 90 5 86
#> 16.44 9.92 17.56 18.29 16.67 7.38 19.34 22.68 10.53 23.41 20.94 16.43 23.81
#> 55 197 149 13 183 166 140 86.1 60.1 88.2 90.1 37 169.1
#> 19.34 21.60 8.37 14.34 9.24 19.98 12.68 23.81 13.15 18.37 20.94 12.52 22.41
#> 77 125 69.1 90.2 130 56.1 37.1 79.1 8 36 18 51 26
#> 7.27 15.65 23.23 20.94 16.47 12.21 12.52 16.23 18.43 21.19 15.21 18.23 15.77
#> 154.1 49 26.1 136 157 92.1 90.3 60.2 181 197.1 187.1 36.1 81.1
#> 12.63 12.19 15.77 21.83 15.10 22.92 20.94 13.15 16.46 21.60 9.92 21.19 14.06
#> 32 37.2 25 25.1 128 167 57.2 43 190.1 136.1 41 190.2 110.1
#> 20.90 12.52 6.32 6.32 20.35 15.55 14.46 12.10 20.81 21.83 18.02 20.81 17.56
#> 140.1 55.1 169.2 20 104 116 132 46 142 94 173 173.1 143
#> 12.68 19.34 22.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 126 72 20.1 152.1 163 72.1 104.1 9 126.1 119 118 72.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 165 120 64 178 67 138 65 27 20.2 71 148 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 138.1 38 173.2 126.2 143.1 2 176 95 151 7 142.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 2.1 174 186 27.1 144 112 65.1 163.1 12 196 118.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 176.2 126.3 120.1 104.2 191.1 182.1 151.1 62 44 174.1 152.2 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.3 143.2 11 160 126.4 7.1 172 75 200 2.2 75.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004409239 0.366085402 0.378953018
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.58498720 0.01252334 0.10454948
#> grade_iii, Cure model
#> 0.29857674
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 36 21.19 1 48 0 1
#> 155 13.08 1 26 0 0
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 129.1 23.41 1 53 1 0
#> 134 17.81 1 47 1 0
#> 37 12.52 1 57 1 0
#> 166 19.98 1 48 0 0
#> 37.1 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 18 15.21 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 66 22.13 1 53 0 0
#> 139 21.49 1 63 1 0
#> 92 22.92 1 47 0 1
#> 14 12.89 1 21 0 0
#> 88 18.37 1 47 0 0
#> 90 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 157 15.10 1 47 0 0
#> 96 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 150 20.33 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 167.1 15.55 1 56 1 0
#> 113.1 22.86 1 34 0 0
#> 5 16.43 1 51 0 1
#> 41 18.02 1 40 1 0
#> 110 17.56 1 65 0 1
#> 111 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 153 21.33 1 55 1 0
#> 55 19.34 1 69 0 1
#> 24 23.89 1 38 0 0
#> 187 9.92 1 39 1 0
#> 155.1 13.08 1 26 0 0
#> 199.1 19.81 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 129.2 23.41 1 53 1 0
#> 79 16.23 1 54 1 0
#> 133 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 76 19.22 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 25 6.32 1 34 1 0
#> 188.1 16.16 1 46 0 1
#> 153.1 21.33 1 55 1 0
#> 177 12.53 1 75 0 0
#> 93.1 10.33 1 52 0 1
#> 125 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 145 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 51 18.23 1 83 0 1
#> 13 14.34 1 54 0 1
#> 29.1 15.45 1 68 1 0
#> 158 20.14 1 74 1 0
#> 111.2 17.45 1 47 0 1
#> 171 16.57 1 41 0 1
#> 190.1 20.81 1 42 1 0
#> 36.2 21.19 1 48 0 1
#> 96.1 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 8 18.43 1 32 0 0
#> 4 17.64 1 NA 0 1
#> 18.1 15.21 1 49 1 0
#> 171.1 16.57 1 41 0 1
#> 6 15.64 1 39 0 0
#> 192.1 16.44 1 31 1 0
#> 155.2 13.08 1 26 0 0
#> 129.3 23.41 1 53 1 0
#> 13.1 14.34 1 54 0 1
#> 124.1 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 5.1 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 199.2 19.81 1 NA 0 1
#> 59.1 10.16 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 183 9.24 1 67 1 0
#> 113.2 22.86 1 34 0 0
#> 32 20.90 1 37 1 0
#> 37.2 12.52 1 57 1 0
#> 133.1 14.65 1 57 0 0
#> 36.3 21.19 1 48 0 1
#> 60 13.15 1 38 1 0
#> 154 12.63 1 20 1 0
#> 111.3 17.45 1 47 0 1
#> 124.2 9.73 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 39.1 15.59 1 37 0 1
#> 123.1 13.00 1 44 1 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 47 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 121.1 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 176 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 17 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 165 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 116.1 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 19 24.00 0 57 0 1
#> 17.1 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 48 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 109 24.00 0 48 0 0
#> 162 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 27.1 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 162.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 21.1 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 141.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 173.1 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 198.1 24.00 0 66 0 1
#> 53.1 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 98.1 24.00 0 34 1 0
#> 200.1 24.00 0 64 0 0
#> 135.1 24.00 0 58 1 0
#> 20.1 24.00 0 46 1 0
#> 103 24.00 0 56 1 0
#> 176.1 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 84.2 24.00 0 39 0 1
#> 120 24.00 0 68 0 1
#> 98.2 24.00 0 34 1 0
#> 146 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 31.2 24.00 0 36 0 1
#> 132.1 24.00 0 55 0 0
#> 160.1 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 27.2 24.00 0 63 1 0
#> 53.2 24.00 0 32 0 1
#> 185.1 24.00 0 44 1 0
#> 27.3 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 121.2 24.00 0 57 1 0
#> 104.1 24.00 0 50 1 0
#> 185.2 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.585 NA NA NA
#> 2 age, Cure model 0.0125 NA NA NA
#> 3 grade_ii, Cure model 0.105 NA NA NA
#> 4 grade_iii, Cure model 0.299 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00441 NA NA NA
#> 2 grade_ii, Survival model 0.366 NA NA NA
#> 3 grade_iii, Survival model 0.379 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.58499 0.01252 0.10455 0.29858
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.58498720 0.01252334 0.10454948 0.29857674
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004409239 0.366085402 0.378953018
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.214072452 0.769531006 0.115571321 0.647913140 0.054086978 0.908660579
#> [7] 0.054086978 0.417212457 0.843960541 0.314960457 0.843960541 0.629144305
#> [13] 0.093065650 0.871586632 0.610304385 0.666644846 0.214072452 0.147066242
#> [19] 0.181288305 0.104431354 0.815939569 0.376121992 0.253619177 0.514989330
#> [25] 0.685291779 0.713512488 0.890150678 0.294455970 0.581644734 0.899413316
#> [31] 0.274425769 0.629144305 0.115571321 0.534144584 0.396760009 0.427360752
#> [37] 0.437485797 0.972690533 0.192541743 0.325269705 0.006384382 0.945382113
#> [43] 0.769531006 0.169970255 0.990910113 0.054086978 0.553186168 0.694703681
#> [49] 0.562767623 0.335553696 0.505226472 0.335553696 0.355623691 0.437485797
#> [55] 0.981810521 0.562767623 0.192541743 0.834611899 0.908660579 0.591197472
#> [61] 0.407021499 0.495426151 0.927001049 0.880876822 0.386442793 0.732191854
#> [67] 0.647913140 0.304715199 0.437485797 0.475959786 0.274425769 0.214072452
#> [73] 0.713512488 0.936209523 0.158604218 0.750799446 0.365853942 0.666644846
#> [79] 0.475959786 0.600738926 0.514989330 0.769531006 0.054086978 0.732191854
#> [85] 0.037863208 0.534144584 0.797359349 0.020827213 0.963563089 0.115571321
#> [91] 0.264068548 0.843960541 0.694703681 0.214072452 0.760177896 0.825292650
#> [97] 0.437485797 0.945382113 0.610304385 0.797359349 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 36 155 113 29 129 93 129.1 134 37 166 37.1 167 69
#> 21.19 13.08 22.86 15.45 23.41 10.33 23.41 17.81 12.52 19.98 12.52 15.55 23.23
#> 42 39 18 36.1 66 139 92 14 88 90 192 157 96
#> 12.43 15.59 15.21 21.19 22.13 21.49 22.92 12.89 18.37 20.94 16.44 15.10 14.54
#> 43 150 100 52 190 167.1 113.1 5 41 110 111 77 153
#> 12.10 20.33 16.07 10.42 20.81 15.55 22.86 16.43 18.02 17.56 17.45 7.27 21.33
#> 55 24 187 155.1 197 91 129.2 79 133 188 76 181 76.1
#> 19.34 23.89 9.92 13.08 21.60 5.33 23.41 16.23 14.65 16.16 19.22 16.46 19.22
#> 179 111.1 25 188.1 153.1 177 93.1 125 40 130 145 49 51
#> 18.63 17.45 6.32 16.16 21.33 12.53 10.33 15.65 18.00 16.47 10.07 12.19 18.23
#> 13 29.1 158 111.2 171 190.1 36.2 96.1 101 136 81 8 18.1
#> 14.34 15.45 20.14 17.45 16.57 20.81 21.19 14.54 9.97 21.83 14.06 18.43 15.21
#> 171.1 6 192.1 155.2 129.3 13.1 86 5.1 123 78 183 113.2 32
#> 16.57 15.64 16.44 13.08 23.41 14.34 23.81 16.43 13.00 23.88 9.24 22.86 20.90
#> 37.2 133.1 36.3 60 154 111.3 187.1 39.1 123.1 121 94 198 132
#> 12.52 14.65 21.19 13.15 12.63 17.45 9.92 15.59 13.00 24.00 24.00 24.00 24.00
#> 47 152 121.1 143 87 176 27 3 160 46 135 17 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 20 22 116 84 83 116.1 122 104 28 19 17.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 72 48 28.1 109 162 98 27.1 141 84.1 152.1 162.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 185 148 200 178 191 21.1 11 141.1 182 173.1 53 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 71 31 98.1 200.1 135.1 20.1 103 176.1 9 84.2 120 98.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 31.1 72.1 31.2 132.1 160.1 80.1 27.2 53.2 185.1 27.3 144 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 185.2 2.1 82
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01395365 0.17733282 0.28475720
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.77515397 0.01537562 -0.07264795
#> grade_iii, Cure model
#> 0.78009684
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 16 8.71 1 71 0 1
#> 181 16.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 153 21.33 1 55 1 0
#> 101 9.97 1 10 0 1
#> 97 19.14 1 65 0 1
#> 16.1 8.71 1 71 0 1
#> 39 15.59 1 37 0 1
#> 32 20.90 1 37 1 0
#> 166 19.98 1 48 0 0
#> 96 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 167.1 15.55 1 56 1 0
#> 4 17.64 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 108 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 97.1 19.14 1 65 0 1
#> 177 12.53 1 75 0 0
#> 86 23.81 1 58 0 1
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 129 23.41 1 53 1 0
#> 158 20.14 1 74 1 0
#> 89 11.44 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 63 22.77 1 31 1 0
#> 113 22.86 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 96.1 14.54 1 33 0 1
#> 79 16.23 1 54 1 0
#> 99 21.19 1 38 0 1
#> 130 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 16.2 8.71 1 71 0 1
#> 39.1 15.59 1 37 0 1
#> 37 12.52 1 57 1 0
#> 4.1 17.64 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 175 21.91 1 43 0 0
#> 177.1 12.53 1 75 0 0
#> 29 15.45 1 68 1 0
#> 101.1 9.97 1 10 0 1
#> 175.1 21.91 1 43 0 0
#> 61.1 10.12 1 36 0 1
#> 89.1 11.44 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 133 14.65 1 57 0 0
#> 181.1 16.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 90 20.94 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 37.1 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 190 20.81 1 42 1 0
#> 194.1 22.40 1 38 0 1
#> 5.2 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 111.1 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 107.1 11.18 1 54 1 0
#> 157 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 177.3 12.53 1 75 0 0
#> 150.1 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 89.2 11.44 1 NA 0 0
#> 153.1 21.33 1 55 1 0
#> 15 22.68 1 48 0 0
#> 195.2 11.76 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 100 16.07 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 58 19.34 1 39 0 0
#> 59.1 10.16 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 15.1 22.68 1 48 0 0
#> 39.2 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 49 12.19 1 48 1 0
#> 133.1 14.65 1 57 0 0
#> 30 17.43 1 78 0 0
#> 14 12.89 1 21 0 0
#> 97.2 19.14 1 65 0 1
#> 108.1 18.29 1 39 0 1
#> 8.1 18.43 1 32 0 0
#> 195.3 11.76 1 NA 1 0
#> 177.4 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 184.1 17.77 1 38 0 0
#> 5.3 16.43 1 51 0 1
#> 52 10.42 1 52 0 1
#> 167.2 15.55 1 56 1 0
#> 8.2 18.43 1 32 0 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 21 24.00 0 47 0 0
#> 67.1 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 161 24.00 0 45 0 0
#> 33.1 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 95.2 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 73.1 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 48.1 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 19 24.00 0 57 0 1
#> 22 24.00 0 52 1 0
#> 75.2 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 7.1 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 137.1 24.00 0 45 1 0
#> 17.2 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 102 24.00 0 49 0 0
#> 147.1 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 95.3 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 67.2 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#> 165.1 24.00 0 47 0 0
#> 95.4 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 2.2 24.00 0 9 0 0
#> 38.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 152.1 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 84.1 24.00 0 39 0 1
#> 71.1 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 102.1 24.00 0 49 0 0
#> 132.2 24.00 0 55 0 0
#> 62.1 24.00 0 71 0 0
#> 3.1 24.00 0 31 1 0
#> 33.2 24.00 0 53 0 0
#> 35.1 24.00 0 51 0 0
#> 138.2 24.00 0 44 1 0
#> 73.2 24.00 0 NA 0 1
#> 67.3 24.00 0 25 0 0
#> 172 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.775 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model -0.0726 NA NA NA
#> 4 grade_iii, Cure model 0.780 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0140 NA NA NA
#> 2 grade_ii, Survival model 0.177 NA NA NA
#> 3 grade_iii, Survival model 0.285 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77515 0.01538 -0.07265 0.78010
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.2
#> Residual Deviance: 242.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77515397 0.01537562 -0.07264795 0.78009684
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01395365 0.17733282 0.28475720
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.88311757 0.98275184 0.72663889 0.80685778 0.45574363 0.96927796
#> [7] 0.59559058 0.98275184 0.78937171 0.51480885 0.56692885 0.85128753
#> [13] 0.99568678 0.80685778 0.86730870 0.64520848 0.96024345 0.59559058
#> [19] 0.88834923 0.19766996 0.74651979 0.74651979 0.23050184 0.55702335
#> [25] 0.14880347 0.92744121 0.38410005 0.57667198 0.31586630 0.29549811
#> [31] 0.95103942 0.85128753 0.77117898 0.48050807 0.71979126 0.97826819
#> [37] 0.98275184 0.78937171 0.91288217 0.53653905 0.40010837 0.86199009
#> [43] 0.31586630 0.96024345 0.42866694 0.88834923 0.82375490 0.96927796
#> [49] 0.42866694 0.95103942 0.48050807 0.84043394 0.72663889 0.69133602
#> [55] 0.50357508 0.23050184 0.91288217 0.67645521 0.88834923 0.52580252
#> [61] 0.40010837 0.74651979 0.73989877 0.69133602 0.83490242 0.92744121
#> [67] 0.82934601 0.66114257 0.88834923 0.53653905 0.94166407 0.45574363
#> [73] 0.35155623 0.93694179 0.27424139 0.66885587 0.77734247 0.77734247
#> [79] 0.62067846 0.58618647 0.71282534 0.35155623 0.78937171 0.87260758
#> [85] 0.92260233 0.84043394 0.70573297 0.87786793 0.59559058 0.64520848
#> [91] 0.62067846 0.88834923 0.08261258 0.67645521 0.74651979 0.94637203
#> [97] 0.80685778 0.62067846 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 154 16 181 167 153 101 97 16.1 39 32 166 96 25
#> 12.63 8.71 16.46 15.55 21.33 9.97 19.14 8.71 15.59 20.90 19.98 14.54 6.32
#> 167.1 81 108 145 97.1 177 86 5 5.1 129 158 78 107
#> 15.55 14.06 18.29 10.07 19.14 12.53 23.81 16.43 16.43 23.41 20.14 23.88 11.18
#> 169 170 63 113 61 96.1 79 99 130 187 16.2 39.1 37
#> 22.41 19.54 22.77 22.86 10.12 14.54 16.23 21.19 16.47 9.92 8.71 15.59 12.52
#> 150 194 57 63.1 145.1 175 177.1 29 101.1 175.1 61.1 36 133
#> 20.33 22.40 14.46 22.77 10.07 21.91 12.53 15.45 9.97 21.91 10.12 21.19 14.65
#> 181.1 111 90 129.1 37.1 184 177.2 190 194.1 5.2 85 111.1 180
#> 16.46 17.45 20.94 23.41 12.52 17.77 12.53 20.81 22.40 16.43 16.44 17.45 14.82
#> 107.1 157 51 177.3 150.1 10 153.1 15 159 69 134 100 100.1
#> 11.18 15.10 18.23 12.53 20.33 10.53 21.33 22.68 10.55 23.23 17.81 16.07 16.07
#> 8 58 45 15.1 39.2 123 49 133.1 30 14 97.2 108.1 8.1
#> 18.43 19.34 17.42 22.68 15.59 13.00 12.19 14.65 17.43 12.89 19.14 18.29 18.43
#> 177.4 24 184.1 5.3 52 167.2 8.2 75 75.1 33 67 21 67.1
#> 12.53 23.89 17.77 16.43 10.42 15.55 18.43 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 48 87 38 64 161 33.1 34 95 185 7 148 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 62 173 132 95.2 138 17 98 165 44 48.1 17.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 118 1 19 22 75.2 54 104 46 185.1 137 152 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 163 137.1 17.2 135 102 147.1 84 95.3 71 22.1 2 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 165.1 95.4 2.1 12 35 31 2.2 38.1 132.1 144 152.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 71.1 191 102.1 132.2 62.1 3.1 33.2 35.1 138.2 67.3 172 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008162726 0.745431663 0.350111641
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.703227347 0.004895239 0.685457107
#> grade_iii, Cure model
#> 1.412146859
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 93 10.33 1 52 0 1
#> 8 18.43 1 32 0 0
#> 18 15.21 1 49 1 0
#> 36 21.19 1 48 0 1
#> 81 14.06 1 34 0 0
#> 66 22.13 1 53 0 0
#> 16 8.71 1 71 0 1
#> 114 13.68 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 99 21.19 1 38 0 1
#> 42 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 130 16.47 1 53 0 1
#> 149 8.37 1 33 1 0
#> 101 9.97 1 10 0 1
#> 134 17.81 1 47 1 0
#> 134.1 17.81 1 47 1 0
#> 164 23.60 1 76 0 1
#> 25 6.32 1 34 1 0
#> 130.1 16.47 1 53 0 1
#> 63 22.77 1 31 1 0
#> 107 11.18 1 54 1 0
#> 158 20.14 1 74 1 0
#> 42.1 12.43 1 49 0 1
#> 13 14.34 1 54 0 1
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 57 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 123 13.00 1 44 1 0
#> 105.1 19.75 1 60 0 0
#> 167 15.55 1 56 1 0
#> 106 16.67 1 49 1 0
#> 16.1 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 18.1 15.21 1 49 1 0
#> 55 19.34 1 69 0 1
#> 130.2 16.47 1 53 0 1
#> 194 22.40 1 38 0 1
#> 88 18.37 1 47 0 0
#> 125 15.65 1 67 1 0
#> 149.1 8.37 1 33 1 0
#> 58.1 19.34 1 39 0 0
#> 39 15.59 1 37 0 1
#> 55.1 19.34 1 69 0 1
#> 140.1 12.68 1 59 1 0
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 93.1 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 52 10.42 1 52 0 1
#> 36.1 21.19 1 48 0 1
#> 81.1 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 16.2 8.71 1 71 0 1
#> 150 20.33 1 48 0 0
#> 51 18.23 1 83 0 1
#> 40.1 18.00 1 28 1 0
#> 68 20.62 1 44 0 0
#> 59 10.16 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 136.1 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 108 18.29 1 39 0 1
#> 158.1 20.14 1 74 1 0
#> 14 12.89 1 21 0 0
#> 49.1 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 25.1 6.32 1 34 1 0
#> 30 17.43 1 78 0 0
#> 77 7.27 1 67 0 1
#> 86 23.81 1 58 0 1
#> 188.1 16.16 1 46 0 1
#> 124.1 9.73 1 NA 1 0
#> 25.2 6.32 1 34 1 0
#> 192.1 16.44 1 31 1 0
#> 134.2 17.81 1 47 1 0
#> 155 13.08 1 26 0 0
#> 92 22.92 1 47 0 1
#> 123.1 13.00 1 44 1 0
#> 181 16.46 1 45 0 1
#> 155.1 13.08 1 26 0 0
#> 197 21.60 1 69 1 0
#> 134.3 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 130.3 16.47 1 53 0 1
#> 167.1 15.55 1 56 1 0
#> 93.2 10.33 1 52 0 1
#> 51.1 18.23 1 83 0 1
#> 16.3 8.71 1 71 0 1
#> 59.1 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 177 12.53 1 75 0 0
#> 86.1 23.81 1 58 0 1
#> 101.1 9.97 1 10 0 1
#> 128 20.35 1 35 0 1
#> 164.1 23.60 1 76 0 1
#> 153 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 78 23.88 1 43 0 0
#> 128.1 20.35 1 35 0 1
#> 24.1 23.89 1 38 0 0
#> 29.1 15.45 1 68 1 0
#> 192.2 16.44 1 31 1 0
#> 30.1 17.43 1 78 0 0
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 12 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 115.1 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 173 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 12.1 24.00 0 63 0 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 102 24.00 0 49 0 0
#> 67 24.00 0 25 0 0
#> 131 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 152 24.00 0 36 0 1
#> 22.1 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 22.2 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 64.1 24.00 0 43 0 0
#> 54 24.00 0 53 1 0
#> 143.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 160.1 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 152.1 24.00 0 36 0 1
#> 53.1 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 121 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 62 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 21.1 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 182.1 24.00 0 35 0 0
#> 143.2 24.00 0 51 0 0
#> 53.2 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 137.1 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 95.1 24.00 0 68 0 1
#> 9.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 33.1 24.00 0 53 0 0
#> 173.1 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 104.2 24.00 0 50 1 0
#> 121.1 24.00 0 57 1 0
#> 104.3 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 122 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 135 24.00 0 58 1 0
#> 34 24.00 0 36 0 0
#> 71.1 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 137.2 24.00 0 45 1 0
#> 143.3 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 94.1 24.00 0 51 0 1
#> 163.1 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.703 NA NA NA
#> 2 age, Cure model 0.00490 NA NA NA
#> 3 grade_ii, Cure model 0.685 NA NA NA
#> 4 grade_iii, Cure model 1.41 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00816 NA NA NA
#> 2 grade_ii, Survival model 0.745 NA NA NA
#> 3 grade_iii, Survival model 0.350 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.703227 0.004895 0.685457 1.412147
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.703227347 0.004895239 0.685457107 1.412146859
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008162726 0.745431663 0.350111641
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.305705286 0.836100928 0.572760983 0.854558076 0.315991731 0.649381152
#> [7] 0.153637729 0.686891553 0.094650852 0.900306200 0.808529823 0.153637729
#> [13] 0.789980314 0.630475750 0.485753109 0.936808975 0.882019644 0.388411567
#> [19] 0.388411567 0.044479324 0.964189857 0.485753109 0.074923551 0.826900566
#> [25] 0.218696916 0.789980314 0.677471200 0.247120416 0.368236594 0.668062191
#> [31] 0.266698152 0.724659973 0.247120416 0.611450774 0.465746863 0.900306200
#> [37] 0.752791648 0.649381152 0.266698152 0.485753109 0.084809890 0.326355754
#> [43] 0.592064739 0.936808975 0.266698152 0.601761601 0.266698152 0.752791648
#> [49] 0.004318246 0.426057657 0.854558076 0.534835657 0.845325892 0.153637729
#> [55] 0.686891553 0.455652645 0.475751618 0.900306200 0.208990427 0.347285258
#> [61] 0.368236594 0.180654075 0.104865437 0.104865437 0.771392708 0.134288481
#> [67] 0.336825739 0.218696916 0.743362174 0.808529823 0.534835657 0.964189857
#> [73] 0.435857906 0.955023208 0.026768470 0.572760983 0.964189857 0.534835657
#> [79] 0.388411567 0.705727437 0.064135267 0.724659973 0.524788786 0.705727437
#> [85] 0.124313275 0.388411567 0.485753109 0.611450774 0.854558076 0.347285258
#> [91] 0.900306200 0.237433268 0.780661182 0.026768470 0.882019644 0.190303034
#> [97] 0.044479324 0.144075028 0.990977743 0.016886674 0.190303034 0.004318246
#> [103] 0.630475750 0.534835657 0.435857906 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 76 10 188 93 8 18 36 81 66 16 49 99 42
#> 19.22 10.53 16.16 10.33 18.43 15.21 21.19 14.06 22.13 8.71 12.19 21.19 12.43
#> 29 130 149 101 134 134.1 164 25 130.1 63 107 158 42.1
#> 15.45 16.47 8.37 9.97 17.81 17.81 23.60 6.32 16.47 22.77 11.18 20.14 12.43
#> 13 105 40 57 58 123 105.1 167 106 16.1 140 18.1 55
#> 14.34 19.75 18.00 14.46 19.34 13.00 19.75 15.55 16.67 8.71 12.68 15.21 19.34
#> 130.2 194 88 125 149.1 58.1 39 55.1 140.1 24 184 93.1 85
#> 16.47 22.40 18.37 15.65 8.37 19.34 15.59 19.34 12.68 23.89 17.77 10.33 16.44
#> 52 36.1 81.1 23 171 16.2 150 51 40.1 68 136 136.1 154
#> 10.42 21.19 14.06 16.92 16.57 8.71 20.33 18.23 18.00 20.62 21.83 21.83 12.63
#> 139 108 158.1 14 49.1 192 25.1 30 77 86 188.1 25.2 192.1
#> 21.49 18.29 20.14 12.89 12.19 16.44 6.32 17.43 7.27 23.81 16.16 6.32 16.44
#> 134.2 155 92 123.1 181 155.1 197 134.3 130.3 167.1 93.2 51.1 16.3
#> 17.81 13.08 22.92 13.00 16.46 13.08 21.60 17.81 16.47 15.55 10.33 18.23 8.71
#> 166 177 86.1 101.1 128 164.1 153 91 78 128.1 24.1 29.1 192.2
#> 19.98 12.53 23.81 9.97 20.35 23.60 21.33 5.33 23.88 20.35 23.89 15.45 16.44
#> 30.1 141 147 12 143 22 161 173 142 35 182 12.1 162
#> 17.43 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 94 102 67 131 116 152 22.1 53 9 162.1 80 22.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 74 64 64.1 54 143.1 185 137 200 112 20 163 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 160.1 80.1 87 152.1 53.1 104 104.1 146 121 28 62 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 21.1 126 182.1 143.2 53.2 27 137.1 71 47 95.1 9.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 132 48 119 33.1 173.1 176 104.2 121.1 104.3 193 122 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 34 71.1 178 137.2 143.3 172 94.1 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00149294 0.79640083 0.15301094
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.41083380 0.02299208 -0.02337979
#> grade_iii, Cure model
#> 1.39996241
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 140 12.68 1 59 1 0
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 108 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 194 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 105 19.75 1 60 0 0
#> 93 10.33 1 52 0 1
#> 23 16.92 1 61 0 0
#> 183 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 194.1 22.40 1 38 0 1
#> 140.1 12.68 1 59 1 0
#> 69 23.23 1 25 0 1
#> 170 19.54 1 43 0 1
#> 15 22.68 1 48 0 0
#> 76 19.22 1 54 0 1
#> 30.1 17.43 1 78 0 0
#> 93.1 10.33 1 52 0 1
#> 111 17.45 1 47 0 1
#> 123 13.00 1 44 1 0
#> 10 10.53 1 34 0 0
#> 76.1 19.22 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 167 15.55 1 56 1 0
#> 194.2 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 96 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 57 14.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 36 21.19 1 48 0 1
#> 50 10.02 1 NA 1 0
#> 18.1 15.21 1 49 1 0
#> 114 13.68 1 NA 0 0
#> 105.2 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 145.1 10.07 1 65 1 0
#> 111.1 17.45 1 47 0 1
#> 43 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 158 20.14 1 74 1 0
#> 61 10.12 1 36 0 1
#> 43.1 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 76.2 19.22 1 54 0 1
#> 194.3 22.40 1 38 0 1
#> 180.1 14.82 1 37 0 0
#> 179 18.63 1 42 0 0
#> 108.1 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 136 21.83 1 43 0 1
#> 76.3 19.22 1 54 0 1
#> 25 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 133 14.65 1 57 0 0
#> 14 12.89 1 21 0 0
#> 168 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 18.2 15.21 1 49 1 0
#> 49 12.19 1 48 1 0
#> 92.1 22.92 1 47 0 1
#> 167.1 15.55 1 56 1 0
#> 61.1 10.12 1 36 0 1
#> 42 12.43 1 49 0 1
#> 140.2 12.68 1 59 1 0
#> 187 9.92 1 39 1 0
#> 32 20.90 1 37 1 0
#> 93.2 10.33 1 52 0 1
#> 127 3.53 1 62 0 1
#> 101.1 9.97 1 10 0 1
#> 164 23.60 1 76 0 1
#> 110.1 17.56 1 65 0 1
#> 117 17.46 1 26 0 1
#> 114.1 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 189 10.51 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 140.3 12.68 1 59 1 0
#> 181.1 16.46 1 45 0 1
#> 5.1 16.43 1 51 0 1
#> 88 18.37 1 47 0 0
#> 177 12.53 1 75 0 0
#> 41 18.02 1 40 1 0
#> 14.1 12.89 1 21 0 0
#> 61.2 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 194.4 22.40 1 38 0 1
#> 181.2 16.46 1 45 0 1
#> 97.1 19.14 1 65 0 1
#> 76.4 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 69.1 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 158.1 20.14 1 74 1 0
#> 177.1 12.53 1 75 0 0
#> 168.1 23.72 1 70 0 0
#> 189.1 10.51 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 13.1 14.34 1 54 0 1
#> 181.3 16.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 94 24.00 0 51 0 1
#> 2 24.00 0 9 0 0
#> 198 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 44 24.00 0 56 0 0
#> 119 24.00 0 17 0 0
#> 191 24.00 0 60 0 1
#> 44.1 24.00 0 56 0 0
#> 71 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 64 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 178.1 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 198.1 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 84 24.00 0 39 0 1
#> 72.1 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 80 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 11 24.00 0 42 0 1
#> 126.1 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 160.2 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 146 24.00 0 63 1 0
#> 147.1 24.00 0 76 1 0
#> 102.1 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 2.1 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 67 24.00 0 25 0 0
#> 74 24.00 0 43 0 1
#> 2.2 24.00 0 9 0 0
#> 118.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 75.1 24.00 0 21 1 0
#> 151.1 24.00 0 42 0 0
#> 109 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 75.2 24.00 0 21 1 0
#> 48.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 64.1 24.00 0 43 0 0
#> 7.1 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 186 24.00 0 45 1 0
#> 182.1 24.00 0 35 0 0
#> 109.1 24.00 0 48 0 0
#> 7.2 24.00 0 37 1 0
#> 12.1 24.00 0 63 0 0
#> 64.2 24.00 0 43 0 0
#> 141.1 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 95.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.41 NA NA NA
#> 2 age, Cure model 0.0230 NA NA NA
#> 3 grade_ii, Cure model -0.0234 NA NA NA
#> 4 grade_iii, Cure model 1.40 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00149 NA NA NA
#> 2 grade_ii, Survival model 0.796 NA NA NA
#> 3 grade_iii, Survival model 0.153 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.41083 0.02299 -0.02338 1.39996
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 238.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.41083380 0.02299208 -0.02337979 1.39996241
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00149294 0.79640083 0.15301094
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.786222986 0.657367889 0.443726898 0.547207633 0.187758827 0.133439756
#> [7] 0.752049060 0.405301620 0.611657445 0.953816420 0.310645137 0.890805023
#> [13] 0.565810781 0.977104165 0.500668238 0.133439756 0.786222986 0.067280014
#> [19] 0.339444746 0.119604239 0.359147105 0.547207633 0.890805023 0.528673800
#> [25] 0.760691659 0.874793459 0.359147105 0.310645137 0.639427278 0.133439756
#> [31] 0.882802083 0.717550881 0.575203651 0.938229222 0.726215396 0.682989290
#> [37] 0.212582551 0.657367889 0.310645137 0.691646265 0.938229222 0.528673800
#> [43] 0.858856718 0.630119735 0.291293259 0.914549183 0.858856718 0.212582551
#> [49] 0.359147105 0.133439756 0.691646265 0.424383853 0.443726898 0.008655384
#> [55] 0.200206288 0.359147105 0.984781142 0.280749109 0.708874914 0.769229827
#> [61] 0.024942005 0.093730843 0.657367889 0.842901066 0.093730843 0.639427278
#> [67] 0.914549183 0.834719530 0.786222986 0.969365999 0.248557751 0.890805023
#> [73] 0.992392389 0.953816420 0.051665121 0.500668238 0.519295596 0.462791784
#> [79] 0.734870658 0.786222986 0.575203651 0.611657445 0.434048070 0.818423437
#> [85] 0.481833624 0.769229827 0.914549183 0.491245950 0.842901066 0.133439756
#> [91] 0.575203651 0.405301620 0.359147105 0.462791784 0.067280014 0.260105251
#> [97] 0.260105251 0.291293259 0.818423437 0.024942005 0.349303038 0.734870658
#> [103] 0.575203651 0.236389554 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 140 18 108 30 175 194 155 97 5 101 105 93 23
#> 12.68 15.21 18.29 17.43 21.91 22.40 13.08 19.14 16.43 9.97 19.75 10.33 16.92
#> 183 110 194.1 140.1 69 170 15 76 30.1 93.1 111 123 10
#> 9.24 17.56 22.40 12.68 23.23 19.54 22.68 19.22 17.43 10.33 17.45 13.00 10.53
#> 76.1 105.1 167 194.2 52 96 181 145 57 157 36 18.1 105.2
#> 19.22 19.75 15.55 22.40 10.42 14.54 16.46 10.07 14.46 15.10 21.19 15.21 19.75
#> 180 145.1 111.1 43 6 158 61 43.1 36.1 76.2 194.3 180.1 179
#> 14.82 10.07 17.45 12.10 15.64 20.14 10.12 12.10 21.19 19.22 22.40 14.82 18.63
#> 108.1 24 136 76.3 25 68 133 14 168 92 18.2 49 92.1
#> 18.29 23.89 21.83 19.22 6.32 20.62 14.65 12.89 23.72 22.92 15.21 12.19 22.92
#> 167.1 61.1 42 140.2 187 32 93.2 127 101.1 164 110.1 117 51
#> 15.55 10.12 12.43 12.68 9.92 20.90 10.33 3.53 9.97 23.60 17.56 17.46 18.23
#> 13 140.3 181.1 5.1 88 177 41 14.1 61.2 184 49.1 194.4 181.2
#> 14.34 12.68 16.46 16.43 18.37 12.53 18.02 12.89 10.12 17.77 12.19 22.40 16.46
#> 97.1 76.4 51.1 69.1 190 190.1 158.1 177.1 168.1 55 13.1 181.3 90
#> 19.14 19.22 18.23 23.23 20.81 20.81 20.14 12.53 23.72 19.34 14.34 16.46 20.94
#> 94 2 198 176 65 143 178 147 72 87 44 119 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 71 53 46 152 64 160 161 200 178.1 75 121 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 62 135 132 120 200.1 198.1 126 20 21 118 144 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 28 102 84 72.1 31 80 135.1 11 126.1 160.1 48 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 146 147.1 102.1 1 2.1 165 12 67 74 2.2 118.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 151 75.1 151.1 109 7 75.2 48.1 176.1 64.1 7.1 33 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 182.1 109.1 7.2 12.1 64.2 141.1 196 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01448405 0.60711855 0.65961209
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.396563441 0.009592431 0.023919449
#> grade_iii, Cure model
#> 0.304303213
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 59 10.16 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 32 20.90 1 37 1 0
#> 93 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 57 14.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 195 11.76 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 51.1 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 41 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 18 15.21 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 110 17.56 1 65 0 1
#> 63 22.77 1 31 1 0
#> 188 16.16 1 46 0 1
#> 180.1 14.82 1 37 0 0
#> 10 10.53 1 34 0 0
#> 96 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 133 14.65 1 57 0 0
#> 187 9.92 1 39 1 0
#> 129 23.41 1 53 1 0
#> 18.1 15.21 1 49 1 0
#> 85 16.44 1 36 0 0
#> 86 23.81 1 58 0 1
#> 51.2 18.23 1 83 0 1
#> 78 23.88 1 43 0 0
#> 180.2 14.82 1 37 0 0
#> 90 20.94 1 50 0 1
#> 117 17.46 1 26 0 1
#> 154 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 36 21.19 1 48 0 1
#> 106 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 85.1 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 111 17.45 1 47 0 1
#> 159.2 10.55 1 50 0 1
#> 154.1 12.63 1 20 1 0
#> 149.1 8.37 1 33 1 0
#> 168 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 58 19.34 1 39 0 0
#> 5 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 190 20.81 1 42 1 0
#> 105 19.75 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 140 12.68 1 59 1 0
#> 153 21.33 1 55 1 0
#> 183.1 9.24 1 67 1 0
#> 164 23.60 1 76 0 1
#> 114.1 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 79 16.23 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 153.1 21.33 1 55 1 0
#> 60 13.15 1 38 1 0
#> 124 9.73 1 NA 1 0
#> 51.3 18.23 1 83 0 1
#> 100.1 16.07 1 60 0 0
#> 168.1 23.72 1 70 0 0
#> 50 10.02 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 139.1 21.49 1 63 1 0
#> 52 10.42 1 52 0 1
#> 157 15.10 1 47 0 0
#> 181 16.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 170 19.54 1 43 0 1
#> 154.2 12.63 1 20 1 0
#> 81 14.06 1 34 0 0
#> 113 22.86 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 159.3 10.55 1 50 0 1
#> 134.1 17.81 1 47 1 0
#> 6 15.64 1 39 0 0
#> 78.2 23.88 1 43 0 0
#> 181.1 16.46 1 45 0 1
#> 140.1 12.68 1 59 1 0
#> 51.4 18.23 1 83 0 1
#> 155 13.08 1 26 0 0
#> 5.1 16.43 1 51 0 1
#> 81.1 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 140.2 12.68 1 59 1 0
#> 57.1 14.46 1 45 0 1
#> 49 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 51.5 18.23 1 83 0 1
#> 79.1 16.23 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 159.4 10.55 1 50 0 1
#> 77 7.27 1 67 0 1
#> 32.2 20.90 1 37 1 0
#> 85.2 16.44 1 36 0 0
#> 15 22.68 1 48 0 0
#> 168.2 23.72 1 70 0 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 19.1 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 53 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 200 24.00 0 64 0 0
#> 22.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 160.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 116 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 196.1 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 147.1 24.00 0 76 1 0
#> 116.1 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 144.1 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#> 22.2 24.00 0 52 1 0
#> 165.1 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 72 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 73.1 24.00 0 NA 0 1
#> 121.1 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 112.2 24.00 0 61 0 0
#> 118 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 83.1 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 64.1 24.00 0 43 0 0
#> 46 24.00 0 71 0 0
#> 98.1 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 53.1 24.00 0 32 0 1
#> 135.1 24.00 0 58 1 0
#> 160.2 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 72.1 24.00 0 40 0 1
#> 9.1 24.00 0 31 1 0
#> 53.2 24.00 0 32 0 1
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 165.2 24.00 0 47 0 0
#> 9.2 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 126 24.00 0 48 0 0
#> 198.2 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 141.1 24.00 0 44 1 0
#> 160.3 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.397 NA NA NA
#> 2 age, Cure model 0.00959 NA NA NA
#> 3 grade_ii, Cure model 0.0239 NA NA NA
#> 4 grade_iii, Cure model 0.304 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0145 NA NA NA
#> 2 grade_ii, Survival model 0.607 NA NA NA
#> 3 grade_iii, Survival model 0.660 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.396563 0.009592 0.023919 0.304303
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 257.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.396563441 0.009592431 0.023919449 0.304303213
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01448405 0.60711855 0.65961209
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.301396507 0.564848846 0.225756781 0.785844815 0.148284177 0.891678070
#> [7] 0.809631220 0.622151066 0.235136161 0.373401826 0.951719371 0.235136161
#> [13] 0.180968037 0.291208903 0.774062567 0.531465587 0.809631220 0.987849979
#> [19] 0.331888066 0.043963342 0.487777259 0.564848846 0.867671622 0.610517273
#> [25] 0.074197844 0.598839164 0.915594564 0.030177810 0.531465587 0.404332595
#> [31] 0.006748160 0.235136161 0.001046136 0.564848846 0.131471308 0.342333508
#> [37] 0.739353224 0.189638353 0.122850273 0.363024353 0.404332595 0.321522771
#> [43] 0.352675746 0.809631220 0.739353224 0.951719371 0.010159454 0.927625118
#> [49] 0.216551722 0.445405057 0.404332595 0.172489207 0.198458599 0.148284177
#> [55] 0.704024680 0.106252909 0.927625118 0.023751284 0.498529007 0.066343976
#> [61] 0.001046136 0.131471308 0.466513849 0.106252909 0.668562536 0.235136161
#> [67] 0.498529007 0.010159454 0.090095408 0.090095408 0.879667531 0.553571146
#> [73] 0.383808935 0.058382593 0.207512519 0.739353224 0.645194495 0.036818856
#> [79] 0.891678070 0.809631220 0.301396507 0.520341086 0.001046136 0.383808935
#> [85] 0.704024680 0.235136161 0.680338366 0.445405057 0.645194495 0.692178508
#> [91] 0.704024680 0.622151066 0.797730538 0.082021474 0.235136161 0.466513849
#> [97] 0.809631220 0.975729865 0.148284177 0.404332595 0.050917120 0.010159454
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 134 180 179 56 32 93 159 57 51 130 149 51.1 68
#> 17.81 14.82 18.63 12.21 20.90 10.33 10.55 14.46 18.23 16.47 8.37 18.23 20.62
#> 41 37 18 159.1 91 110 63 188 180.1 10 96 136 133
#> 18.02 12.52 15.21 10.55 5.33 17.56 22.77 16.16 14.82 10.53 14.54 21.83 14.65
#> 187 129 18.1 85 86 51.2 78 180.2 90 117 154 158 36
#> 9.92 23.41 15.21 16.44 23.81 18.23 23.88 14.82 20.94 17.46 12.63 20.14 21.19
#> 106 85.1 184 111 159.2 154.1 149.1 168 183 58 5 192 190
#> 16.67 16.44 17.77 17.45 10.55 12.63 8.37 23.72 9.24 19.34 16.43 16.44 20.81
#> 105 32.1 140 153 183.1 164 100 194 78.1 90.1 79 153.1 60
#> 19.75 20.90 12.68 21.33 9.24 23.60 16.07 22.40 23.88 20.94 16.23 21.33 13.15
#> 51.3 100.1 168.1 139 139.1 52 157 181 169 170 154.2 81 113
#> 18.23 16.07 23.72 21.49 21.49 10.42 15.10 16.46 22.41 19.54 12.63 14.06 22.86
#> 93.1 159.3 134.1 6 78.2 181.1 140.1 51.4 155 5.1 81.1 123 140.2
#> 10.33 10.55 17.81 15.64 23.88 16.46 12.68 18.23 13.08 16.43 14.06 13.00 12.68
#> 57.1 49 197 51.5 79.1 159.4 77 32.2 85.2 15 168.2 156 27
#> 14.46 12.19 21.60 18.23 16.23 10.55 7.27 20.90 16.44 22.68 23.72 24.00 24.00
#> 112 196 148 19 141 160 112.1 147 176 19.1 3 47 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 22 146 98 200 22.1 121 160.1 152 198 116 65 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 144 147.1 116.1 83 144.1 165 152.1 22.2 165.1 104 9 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 72 120 121.1 109 112.2 118 198.1 83.1 122 21 64 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 98.1 135 28 138 148.1 53.1 135.1 160.2 95 132 33.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 72.1 9.1 53.2 82 84 178 165.2 9.2 103 2.1 126 198.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 141.1 160.3 17 67 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001351376 0.127766948 0.078525223
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.38397932 0.00331342 0.08497947
#> grade_iii, Cure model
#> 1.21857404
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 190 20.81 1 42 1 0
#> 171 16.57 1 41 0 1
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 154 12.63 1 20 1 0
#> 56 12.21 1 60 0 0
#> 159 10.55 1 50 0 1
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 170 19.54 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 23 16.92 1 61 0 0
#> 13 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 154.1 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 93 10.33 1 52 0 1
#> 158 20.14 1 74 1 0
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 187 9.92 1 39 1 0
#> 158.1 20.14 1 74 1 0
#> 105 19.75 1 60 0 0
#> 183.1 9.24 1 67 1 0
#> 154.2 12.63 1 20 1 0
#> 10 10.53 1 34 0 0
#> 127 3.53 1 62 0 1
#> 105.1 19.75 1 60 0 0
#> 113 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 130.1 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 145 10.07 1 65 1 0
#> 56.1 12.21 1 60 0 0
#> 130.2 16.47 1 53 0 1
#> 133 14.65 1 57 0 0
#> 42.1 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 61 10.12 1 36 0 1
#> 164 23.60 1 76 0 1
#> 81 14.06 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 105.2 19.75 1 60 0 0
#> 97 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 61.2 10.12 1 36 0 1
#> 199.1 19.81 1 NA 0 1
#> 127.1 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 171.1 16.57 1 41 0 1
#> 40 18.00 1 28 1 0
#> 139 21.49 1 63 1 0
#> 134.1 17.81 1 47 1 0
#> 139.1 21.49 1 63 1 0
#> 175.1 21.91 1 43 0 0
#> 155 13.08 1 26 0 0
#> 45 17.42 1 54 0 1
#> 136 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 133.1 14.65 1 57 0 0
#> 189.1 10.51 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 199.2 19.81 1 NA 0 1
#> 189.2 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 49.1 12.19 1 48 1 0
#> 36 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 183.2 9.24 1 67 1 0
#> 25 6.32 1 34 1 0
#> 26.1 15.77 1 49 0 1
#> 158.2 20.14 1 74 1 0
#> 56.2 12.21 1 60 0 0
#> 10.1 10.53 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 179.1 18.63 1 42 0 0
#> 69 23.23 1 25 0 1
#> 175.2 21.91 1 43 0 0
#> 189.3 10.51 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 59.1 10.16 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 110 17.56 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 39 15.59 1 37 0 1
#> 23.1 16.92 1 61 0 0
#> 189.4 10.51 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 60 13.15 1 38 1 0
#> 111 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 39.1 15.59 1 37 0 1
#> 88 18.37 1 47 0 0
#> 88.1 18.37 1 47 0 0
#> 149 8.37 1 33 1 0
#> 113.1 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 69.1 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 22 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 142 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 38 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 72 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 22.2 24.00 0 52 1 0
#> 1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 35 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 12 24.00 0 63 0 0
#> 176.1 24.00 0 43 0 1
#> 122 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 67.1 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 104.1 24.00 0 50 1 0
#> 34.1 24.00 0 36 0 0
#> 28.1 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 122.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 35.1 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 12.1 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 95.1 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 28.2 24.00 0 67 1 0
#> 165 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 48 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 104.2 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 84 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 103.1 24.00 0 56 1 0
#> 47.1 24.00 0 38 0 1
#> 137.1 24.00 0 45 1 0
#> 9.2 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 112.2 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 87.2 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 132.1 24.00 0 55 0 0
#> 103.2 24.00 0 56 1 0
#> 118.1 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 47.2 24.00 0 38 0 1
#> 44.1 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 28.3 24.00 0 67 1 0
#> 7 24.00 0 37 1 0
#> 28.4 24.00 0 67 1 0
#> 27 24.00 0 63 1 0
#> 12.2 24.00 0 63 0 0
#> 198 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.384 NA NA NA
#> 2 age, Cure model 0.00331 NA NA NA
#> 3 grade_ii, Cure model 0.0850 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00135 NA NA NA
#> 2 grade_ii, Survival model 0.128 NA NA NA
#> 3 grade_iii, Survival model 0.0785 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.383979 0.003313 0.084979 1.218574
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.9
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.38397932 0.00331342 0.08497947 1.21857404
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001351376 0.127766948 0.078525223
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74373733 0.79293250 0.20903408 0.46611604 0.48594065 0.19898866
#> [7] 0.69458378 0.76345673 0.81267488 0.10055538 0.93095013 0.28677713
#> [13] 0.53533411 0.43621914 0.65459576 0.90157793 0.53533411 0.35644227
#> [19] 0.69458378 0.51536038 0.52534881 0.38639155 0.84236795 0.22908321
#> [25] 0.60480313 0.89166655 0.22908321 0.25780292 0.90157793 0.69458378
#> [31] 0.82260542 0.98035587 0.25780292 0.07048034 0.48594065 0.61477419
#> [37] 0.88174658 0.76345673 0.48594065 0.62475315 0.74373733 0.18890217
#> [43] 0.02135355 0.31680218 0.64459836 0.45608602 0.85230689 0.00766561
#> [49] 0.66459232 0.85230689 0.25780292 0.30678601 0.09019649 0.85230689
#> [55] 0.98035587 0.13931580 0.46611604 0.37633532 0.14956684 0.38639155
#> [61] 0.14956684 0.10055538 0.68458718 0.42620653 0.12903856 0.95073584
#> [67] 0.62475315 0.35644227 0.72401148 0.79293250 0.16925678 0.55517565
#> [73] 0.90157793 0.96061482 0.55517565 0.22908321 0.76345673 0.82260542
#> [79] 0.02135355 0.31680218 0.04077749 0.10055538 0.72401148 0.59482162
#> [85] 0.40617508 0.97048515 0.57500849 0.43621914 0.16925678 0.67459563
#> [91] 0.41619262 0.29677290 0.57500849 0.33658615 0.33658615 0.94084750
#> [97] 0.07048034 0.05997920 0.04077749 0.21904420 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 42 49 190 171 130 32 154 56 159 175 16 170 100
#> 12.43 12.19 20.81 16.57 16.47 20.90 12.63 12.21 10.55 21.91 8.71 19.54 16.07
#> 23 13 183 100.1 51 154.1 79 188 134 93 158 18 187
#> 16.92 14.34 9.24 16.07 18.23 12.63 16.23 16.16 17.81 10.33 20.14 15.21 9.92
#> 158.1 105 183.1 154.2 10 127 105.1 113 130.1 180 145 56.1 130.2
#> 20.14 19.75 9.24 12.63 10.53 3.53 19.75 22.86 16.47 14.82 10.07 12.21 16.47
#> 133 42.1 90 129 179 57 106 61 164 81 61.1 105.2 97
#> 14.65 12.43 20.94 23.41 18.63 14.46 16.67 10.12 23.60 14.06 10.12 19.75 19.14
#> 63 61.2 127.1 197 171.1 40 139 134.1 139.1 175.1 155 45 136
#> 22.77 10.12 3.53 21.60 16.57 18.00 21.49 17.81 21.49 21.91 13.08 17.42 21.83
#> 70 133.1 51.1 37 49.1 36 26 183.2 25 26.1 158.2 56.2 10.1
#> 7.38 14.65 18.23 12.52 12.19 21.19 15.77 9.24 6.32 15.77 20.14 12.21 10.53
#> 129.1 179.1 69 175.2 37.1 167 110 91 39 23.1 99 60 111
#> 23.41 18.63 23.23 21.91 12.52 15.55 17.56 5.33 15.59 16.92 21.19 13.15 17.45
#> 58 39.1 88 88.1 149 113.1 92 69.1 150 22 22.1 28 151
#> 19.34 15.59 18.37 18.37 8.37 22.86 22.92 23.23 20.33 24.00 24.00 24.00 24.00
#> 142 54 38 176 112 72 160 9 98 22.2 1 126 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 35 161 12 176.1 122 146 163 148 34 87 67.1 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 2 109 104.1 34.1 28.1 135 122.1 103 47 87.1 35.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 178.1 163.1 118 38.1 112.1 132 137 12.1 144 95.1 186 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 200 48 95.2 104.2 44 84 156 143 103.1 47.1 137.1 9.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 112.2 80 87.2 142.1 132.1 103.2 118.1 17 47.2 44.1 102 28.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 28.4 27 12.2 198 94
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007944391 1.027370937 0.723194667
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.313657209 -0.005652864 -0.254387612
#> grade_iii, Cure model
#> 0.738342010
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 117 17.46 1 26 0 1
#> 77 7.27 1 67 0 1
#> 23 16.92 1 61 0 0
#> 56 12.21 1 60 0 0
#> 24 23.89 1 38 0 0
#> 57 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 110 17.56 1 65 0 1
#> 42 12.43 1 49 0 1
#> 166 19.98 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 45 17.42 1 54 0 1
#> 106 16.67 1 49 1 0
#> 15 22.68 1 48 0 0
#> 60 13.15 1 38 1 0
#> 90 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 88 18.37 1 47 0 0
#> 105 19.75 1 60 0 0
#> 101 9.97 1 10 0 1
#> 197 21.60 1 69 1 0
#> 167.1 15.55 1 56 1 0
#> 123 13.00 1 44 1 0
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 166.1 19.98 1 48 0 0
#> 153 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 139 21.49 1 63 1 0
#> 128 20.35 1 35 0 1
#> 37 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 127 3.53 1 62 0 1
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 85 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 117.1 17.46 1 26 0 1
#> 168 23.72 1 70 0 0
#> 15.1 22.68 1 48 0 0
#> 180 14.82 1 37 0 0
#> 81 14.06 1 34 0 0
#> 113 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 59 10.16 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 66 22.13 1 53 0 0
#> 179.1 18.63 1 42 0 0
#> 199 19.81 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 14 12.89 1 21 0 0
#> 169.2 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 110.1 17.56 1 65 0 1
#> 101.1 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 134.1 17.81 1 47 1 0
#> 180.1 14.82 1 37 0 0
#> 76 19.22 1 54 0 1
#> 128.1 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 107.1 11.18 1 54 1 0
#> 158 20.14 1 74 1 0
#> 179.2 18.63 1 42 0 0
#> 145 10.07 1 65 1 0
#> 91 5.33 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 77.1 7.27 1 67 0 1
#> 6.1 15.64 1 39 0 0
#> 42.1 12.43 1 49 0 1
#> 179.3 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 16 8.71 1 71 0 1
#> 153.1 21.33 1 55 1 0
#> 91.1 5.33 1 61 0 1
#> 179.4 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 88.1 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 136 21.83 1 43 0 1
#> 199.1 19.81 1 NA 0 1
#> 128.2 20.35 1 35 0 1
#> 154.1 12.63 1 20 1 0
#> 70.1 7.38 1 30 1 0
#> 68 20.62 1 44 0 0
#> 89.2 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 88.2 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 40 18.00 1 28 1 0
#> 169.3 22.41 1 46 0 0
#> 26.1 15.77 1 49 0 1
#> 105.1 19.75 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 42.2 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 105.2 19.75 1 60 0 0
#> 49.1 12.19 1 48 1 0
#> 24.1 23.89 1 38 0 0
#> 161 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 87.1 24.00 0 27 0 0
#> 20.1 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 27 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 120 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 34.1 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 73.1 24.00 0 NA 0 1
#> 178.1 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 178.2 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 161.1 24.00 0 45 0 0
#> 147 24.00 0 76 1 0
#> 53 24.00 0 32 0 1
#> 165.1 24.00 0 47 0 0
#> 34.2 24.00 0 36 0 0
#> 83 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 147.1 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 28 24.00 0 67 1 0
#> 126 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 54.2 24.00 0 53 1 0
#> 65.1 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 46.1 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 141.1 24.00 0 44 1 0
#> 34.3 24.00 0 36 0 0
#> 46.2 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 119 24.00 0 17 0 0
#> 137 24.00 0 45 1 0
#> 11.1 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 198 24.00 0 66 0 1
#> 191.1 24.00 0 60 0 1
#> 102 24.00 0 49 0 0
#> 143.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 116.1 24.00 0 58 0 1
#> 141.2 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 178.3 24.00 0 52 1 0
#> 34.4 24.00 0 36 0 0
#> 65.2 24.00 0 57 1 0
#> 1.1 24.00 0 23 1 0
#> 44.1 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 22.1 24.00 0 52 1 0
#> 102.1 24.00 0 49 0 0
#> 135 24.00 0 58 1 0
#> 47 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.314 NA NA NA
#> 2 age, Cure model -0.00565 NA NA NA
#> 3 grade_ii, Cure model -0.254 NA NA NA
#> 4 grade_iii, Cure model 0.738 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00794 NA NA NA
#> 2 grade_ii, Survival model 1.03 NA NA NA
#> 3 grade_iii, Survival model 0.723 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.313657 -0.005653 -0.254388 0.738342
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.313657209 -0.005652864 -0.254387612 0.738342010
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007944391 1.027370937 0.723194667
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.559369161 0.953009075 0.588398921 0.820245922 0.005215095 0.702349222
#> [7] 0.045724526 0.539570721 0.794317443 0.331615715 0.862981510 0.888068081
#> [13] 0.655423465 0.578704819 0.598154756 0.092821583 0.730626720 0.259387322
#> [19] 0.846138770 0.115560841 0.466223781 0.352092668 0.912876719 0.201400920
#> [25] 0.655423465 0.749254676 0.519604061 0.414886827 0.331615715 0.226389177
#> [31] 0.739929758 0.383377732 0.214147581 0.281228411 0.785463009 0.070735530
#> [37] 0.992201795 0.879698529 0.115560841 0.607770566 0.767699387 0.559369161
#> [43] 0.031839165 0.092821583 0.674069692 0.721195708 0.081600857 0.020165345
#> [49] 0.059128954 0.888068081 0.161716550 0.414886827 0.692848239 0.758468415
#> [55] 0.115560841 0.404457362 0.617424369 0.539570721 0.912876719 0.636348334
#> [61] 0.161716550 0.498420446 0.519604061 0.674069692 0.393965759 0.281228411
#> [67] 0.711793799 0.846138770 0.321417137 0.414886827 0.904615465 0.976635063
#> [73] 0.862981510 0.953009075 0.636348334 0.794317443 0.414886827 0.937176427
#> [79] 0.929060988 0.226389177 0.976635063 0.414886827 0.248354034 0.466223781
#> [85] 0.311036822 0.188138692 0.281228411 0.767699387 0.937176427 0.270242757
#> [91] 0.968786591 0.466223781 0.829016866 0.509148452 0.115560841 0.617424369
#> [97] 0.352092668 0.794317443 0.352092668 0.829016866 0.005215095 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 117 77 23 56 24 57 164 110 42 166 159 93 167
#> 17.46 7.27 16.92 12.21 23.89 14.46 23.60 17.56 12.43 19.98 10.55 10.33 15.55
#> 45 106 15 60 90 107 169 88 105 101 197 167.1 123
#> 17.42 16.67 22.68 13.15 20.94 11.18 22.41 18.37 19.75 9.97 21.60 15.55 13.00
#> 134 179 166.1 153 155 170 139 128 37 92 127 52 169.1
#> 17.81 18.63 19.98 21.33 13.08 19.54 21.49 20.35 12.52 22.92 3.53 10.42 22.41
#> 85 154 117.1 168 15.1 180 81 113 78 69 93.1 66 179.1
#> 16.44 12.63 17.46 23.72 22.68 14.82 14.06 22.86 23.88 23.23 10.33 22.13 18.63
#> 133 14 169.2 97 26 110.1 101.1 6 66.1 41 134.1 180.1 76
#> 14.65 12.89 22.41 19.14 15.77 17.56 9.97 15.64 22.13 18.02 17.81 14.82 19.22
#> 128.1 13 107.1 158 179.2 145 91 159.1 77.1 6.1 42.1 179.3 70
#> 20.35 14.34 11.18 20.14 18.63 10.07 5.33 10.55 7.27 15.64 12.43 18.63 7.38
#> 16 153.1 91.1 179.4 36 88.1 150 136 128.2 154.1 70.1 68 25
#> 8.71 21.33 5.33 18.63 21.19 18.37 20.33 21.83 20.35 12.63 7.38 20.62 6.32
#> 88.2 49 40 169.3 26.1 105.1 42.2 105.2 49.1 24.1 161 20 138
#> 18.37 12.19 18.00 22.41 15.77 19.75 12.43 19.75 12.19 23.89 24.00 24.00 24.00
#> 87 34 87.1 20.1 143 178 142 35 54 132 27 11 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 122 165 104 191 65 178.1 54.1 84 178.2 176 161.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 165.1 34.2 83 3 131 2 141 1 46 156 193 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 28 126 7 54.2 65.1 116 46.1 22 176.1 141.1 34.3 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 200 119 137 11.1 132.1 198 191.1 102 143.1 17 82 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 122.1 152 71 178.3 34.4 65.2 1.1 44.1 62 160 64 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 102.1 135 47
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01659420 0.60604300 -0.03412369
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.167500866 0.004940755 -0.244362724
#> grade_iii, Cure model
#> 0.574444375
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 139 21.49 1 63 1 0
#> 85 16.44 1 36 0 0
#> 129 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 60 13.15 1 38 1 0
#> 117 17.46 1 26 0 1
#> 86.1 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 25 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 139.1 21.49 1 63 1 0
#> 14 12.89 1 21 0 0
#> 130 16.47 1 53 0 1
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 134 17.81 1 47 1 0
#> 86.2 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 187.1 9.92 1 39 1 0
#> 39 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 78 23.88 1 43 0 0
#> 124 9.73 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 140 12.68 1 59 1 0
#> 59.1 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 125 15.65 1 67 1 0
#> 59.2 10.16 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 63 22.77 1 31 1 0
#> 86.3 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 113 22.86 1 34 0 0
#> 139.2 21.49 1 63 1 0
#> 107 11.18 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 169 22.41 1 46 0 0
#> 56 12.21 1 60 0 0
#> 169.1 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 188.1 16.16 1 46 0 1
#> 14.1 12.89 1 21 0 0
#> 130.1 16.47 1 53 0 1
#> 23 16.92 1 61 0 0
#> 105.1 19.75 1 60 0 0
#> 14.2 12.89 1 21 0 0
#> 81 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 14.3 12.89 1 21 0 0
#> 78.1 23.88 1 43 0 0
#> 169.2 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 14.4 12.89 1 21 0 0
#> 111.1 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 168 23.72 1 70 0 0
#> 187.2 9.92 1 39 1 0
#> 91.2 5.33 1 61 0 1
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 30 17.43 1 78 0 0
#> 85.2 16.44 1 36 0 0
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 164.1 23.60 1 76 0 1
#> 30.1 17.43 1 78 0 0
#> 69.1 23.23 1 25 0 1
#> 76 19.22 1 54 0 1
#> 154.1 12.63 1 20 1 0
#> 169.3 22.41 1 46 0 0
#> 189.1 10.51 1 NA 1 0
#> 189.2 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 49 12.19 1 48 1 0
#> 166 19.98 1 48 0 0
#> 86.4 23.81 1 58 0 1
#> 50 10.02 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 134.1 17.81 1 47 1 0
#> 25.1 6.32 1 34 1 0
#> 168.1 23.72 1 70 0 0
#> 108.1 18.29 1 39 0 1
#> 16 8.71 1 71 0 1
#> 76.1 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 79 16.23 1 54 1 0
#> 14.5 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 184.1 17.77 1 38 0 0
#> 194.1 22.40 1 38 0 1
#> 153 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 125.1 15.65 1 67 1 0
#> 92.1 22.92 1 47 0 1
#> 39.1 15.59 1 37 0 1
#> 129.1 23.41 1 53 1 0
#> 74 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 144 24.00 0 28 0 1
#> 104 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 72 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 138.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 120 24.00 0 68 0 1
#> 73.1 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 121 24.00 0 57 1 0
#> 121.1 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 67 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 162 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 44.1 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 112.1 24.00 0 61 0 0
#> 162.1 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 193.1 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 65.1 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 119.1 24.00 0 17 0 0
#> 67.1 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 67.2 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 144.1 24.00 0 28 0 1
#> 193.2 24.00 0 45 0 1
#> 1.1 24.00 0 23 1 0
#> 65.2 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 83.1 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 198.2 24.00 0 66 0 1
#> 72.1 24.00 0 40 0 1
#> 112.2 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 104.1 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 185.2 24.00 0 44 1 0
#> 112.3 24.00 0 61 0 0
#> 146.1 24.00 0 63 1 0
#> 62.1 24.00 0 71 0 0
#> 27.1 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 17.1 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 17.2 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 35.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.168 NA NA NA
#> 2 age, Cure model 0.00494 NA NA NA
#> 3 grade_ii, Cure model -0.244 NA NA NA
#> 4 grade_iii, Cure model 0.574 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0166 NA NA NA
#> 2 grade_ii, Survival model 0.606 NA NA NA
#> 3 grade_iii, Survival model -0.0341 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.167501 0.004941 -0.244363 0.574444
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 250 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.167500866 0.004940755 -0.244362724 0.574444375
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01659420 0.60604300 -0.03412369
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.417881e-03 8.305056e-02 3.408698e-01 1.614569e-02 7.139410e-02
#> [6] 4.668561e-02 2.522630e-01 5.683311e-01 2.326709e-01 1.417881e-03
#> [11] 4.402704e-01 9.147299e-01 1.288331e-01 8.305056e-02 5.984923e-01
#> [16] 3.172305e-01 8.317014e-01 1.038421e-02 1.954374e-01 1.417881e-03
#> [21] 1.774688e-01 8.484317e-01 8.484317e-01 4.952900e-01 2.136747e-01
#> [26] 8.151149e-01 3.777539e-04 3.408698e-01 3.057066e-01 6.875776e-01
#> [31] 2.246759e-02 4.674588e-01 1.078008e-01 4.219175e-02 1.417881e-03
#> [36] 9.483111e-01 3.765201e-02 8.305056e-02 7.987214e-01 2.326709e-01
#> [41] 7.342834e-01 4.141011e-01 5.143042e-02 7.661618e-01 5.143042e-02
#> [46] 7.501258e-01 4.141011e-01 5.984923e-01 3.172305e-01 2.944004e-01
#> [51] 1.288331e-01 5.984923e-01 5.533285e-01 3.885147e-01 5.984923e-01
#> [56] 3.777539e-04 5.143042e-02 1.145751e-01 5.984923e-01 2.522630e-01
#> [61] 9.483111e-01 6.285508e-03 8.484317e-01 9.483111e-01 5.771652e-05
#> [66] 2.951639e-02 7.034094e-01 2.727413e-01 3.408698e-01 1.686959e-01
#> [71] 1.601072e-01 1.038421e-02 2.727413e-01 2.246759e-02 1.439561e-01
#> [76] 7.034094e-01 5.143042e-02 5.238879e-01 7.824122e-01 1.215894e-01
#> [81] 1.417881e-03 4.402704e-01 1.954374e-01 9.147299e-01 6.285508e-03
#> [86] 1.774688e-01 8.977555e-01 1.439561e-01 5.384993e-01 4.012566e-01
#> [91] 5.984923e-01 5.833434e-01 2.136747e-01 7.139410e-02 1.012272e-01
#> [96] 3.408698e-01 4.674588e-01 2.951639e-02 4.952900e-01 1.614569e-02
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 86 139 85 129 194 15 111 60 117 86.1 100 25 105
#> 23.81 21.49 16.44 23.41 22.40 22.68 17.45 13.15 17.46 23.81 16.07 6.32 19.75
#> 139.1 14 130 10 164 134 86.2 108 187 187.1 39 184 159
#> 21.49 12.89 16.47 10.53 23.60 17.81 23.81 18.29 9.92 9.92 15.59 17.77 10.55
#> 78 85.1 171 140 69 125 99 63 86.3 91 113 139.2 107
#> 23.88 16.44 16.57 12.68 23.23 15.65 21.19 22.77 23.81 5.33 22.86 21.49 11.18
#> 117.1 177 188 169 56 169.1 42 188.1 14.1 130.1 23 105.1 14.2
#> 17.46 12.53 16.16 22.41 12.21 22.41 12.43 16.16 12.89 16.47 16.92 19.75 12.89
#> 81 5 14.3 78.1 169.2 90 14.4 111.1 91.1 168 187.2 91.2 24
#> 14.06 16.43 12.89 23.88 22.41 20.94 12.89 17.45 5.33 23.72 9.92 5.33 23.89
#> 92 154 30 85.2 8 97 164.1 30.1 69.1 76 154.1 169.3 167
#> 22.92 12.63 17.43 16.44 18.43 19.14 23.60 17.43 23.23 19.22 12.63 22.41 15.55
#> 49 166 86.4 100.1 134.1 25.1 168.1 108.1 16 76.1 157 79 14.5
#> 12.19 19.98 23.81 16.07 17.81 6.32 23.72 18.29 8.71 19.22 15.10 16.23 12.89
#> 155 184.1 194.1 153 192 125.1 92.1 39.1 129.1 74 31 144 104
#> 13.08 17.77 22.40 21.33 16.44 15.65 22.92 15.59 23.41 24.00 24.00 24.00 24.00
#> 83 72 19 9 54 118 138 185 1 17 44 178 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 120 84 131 112 121 121.1 71 65 198 67 132 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 193 162 148 44.1 102 112.1 162.1 122 119 193.1 161 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 156 198.1 65.1 109 119.1 67.1 185.1 67.2 75 144.1 193.2 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 71.1 98 143 27 34 83.1 35 198.2 72.1 112.2 126 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 165 185.2 112.3 146.1 62.1 27.1 38 176 38.1 87 17.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 53 35.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008241776 1.045733845 0.680644764
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.5811244360 0.0001778573 0.7109923947
#> grade_iii, Cure model
#> 1.4565610885
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 123 13.00 1 44 1 0
#> 187 9.92 1 39 1 0
#> 108 18.29 1 39 0 1
#> 39 15.59 1 37 0 1
#> 45 17.42 1 54 0 1
#> 55 19.34 1 69 0 1
#> 166 19.98 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 89 11.44 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 140 12.68 1 59 1 0
#> 55.1 19.34 1 69 0 1
#> 61 10.12 1 36 0 1
#> 39.1 15.59 1 37 0 1
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 183 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 128 20.35 1 35 0 1
#> 199 19.81 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 108.1 18.29 1 39 0 1
#> 49.1 12.19 1 48 1 0
#> 55.2 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 76 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 49.2 12.19 1 48 1 0
#> 150 20.33 1 48 0 0
#> 24 23.89 1 38 0 0
#> 179 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 134 17.81 1 47 1 0
#> 179.1 18.63 1 42 0 0
#> 42 12.43 1 49 0 1
#> 66.1 22.13 1 53 0 0
#> 171 16.57 1 41 0 1
#> 45.1 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 4.1 17.64 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 124 9.73 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 36.1 21.19 1 48 0 1
#> 189.1 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 194.1 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 125 15.65 1 67 1 0
#> 108.2 18.29 1 39 0 1
#> 45.2 17.42 1 54 0 1
#> 199.1 19.81 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 25 6.32 1 34 1 0
#> 92.1 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 158 20.14 1 74 1 0
#> 4.2 17.64 1 NA 0 1
#> 78.1 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 130 16.47 1 53 0 1
#> 6 15.64 1 39 0 0
#> 56 12.21 1 60 0 0
#> 199.2 19.81 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 8.1 18.43 1 32 0 0
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 168.1 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 57 14.46 1 45 0 1
#> 32.1 20.90 1 37 1 0
#> 125.1 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 26.1 15.77 1 49 0 1
#> 189.2 10.51 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 70.1 7.38 1 30 1 0
#> 29 15.45 1 68 1 0
#> 140.1 12.68 1 59 1 0
#> 183.1 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 123.1 13.00 1 44 1 0
#> 91.1 5.33 1 61 0 1
#> 127 3.53 1 62 0 1
#> 36.2 21.19 1 48 0 1
#> 70.2 7.38 1 30 1 0
#> 13 14.34 1 54 0 1
#> 169 22.41 1 46 0 0
#> 101.1 9.97 1 10 0 1
#> 79.1 16.23 1 54 1 0
#> 154 12.63 1 20 1 0
#> 55.3 19.34 1 69 0 1
#> 127.1 3.53 1 62 0 1
#> 153 21.33 1 55 1 0
#> 4.3 17.64 1 NA 0 1
#> 124.1 9.73 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 188 16.16 1 46 0 1
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 62 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 94.1 24.00 0 51 0 1
#> 103 24.00 0 56 1 0
#> 165.1 24.00 0 47 0 0
#> 19.1 24.00 0 57 0 1
#> 182 24.00 0 35 0 0
#> 162.1 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 122.1 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 2.1 24.00 0 9 0 0
#> 142.1 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 94.2 24.00 0 51 0 1
#> 98 24.00 0 34 1 0
#> 163 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 142.2 24.00 0 53 0 0
#> 146.1 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 95.1 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 182.1 24.00 0 35 0 0
#> 62.1 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 163.1 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 95.2 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 62.2 24.00 0 71 0 0
#> 122.2 24.00 0 66 0 0
#> 146.2 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 98.1 24.00 0 34 1 0
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 87 24.00 0 27 0 0
#> 7.1 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 141 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 75.1 24.00 0 21 1 0
#> 22 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 75.2 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 75.3 24.00 0 21 1 0
#> 71.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 163.2 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 120.2 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 161.1 24.00 0 45 0 0
#> 115 24.00 0 NA 1 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 115.1 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.581 NA NA NA
#> 2 age, Cure model 0.000178 NA NA NA
#> 3 grade_ii, Cure model 0.711 NA NA NA
#> 4 grade_iii, Cure model 1.46 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00824 NA NA NA
#> 2 grade_ii, Survival model 1.05 NA NA NA
#> 3 grade_iii, Survival model 0.681 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5811244 0.0001779 0.7109924 1.4565611
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 238.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5811244360 0.0001778573 0.7109923947 1.4565610885
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008241776 1.045733845 0.680644764
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.627771771 0.744912218 0.771297085 0.910389068 0.522949452 0.709478159
#> [7] 0.561688013 0.424510182 0.394124093 0.184214255 0.846843721 0.143035207
#> [13] 0.796936538 0.424510182 0.886767509 0.709478159 0.618325736 0.664461479
#> [19] 0.018205258 0.918175637 0.249668507 0.353105298 0.062583277 0.878760491
#> [25] 0.332177775 0.114539990 0.522949452 0.846843721 0.424510182 0.404471071
#> [31] 0.463222487 0.209669489 0.846843721 0.373454189 0.004636374 0.483070226
#> [37] 0.287283034 0.551993117 0.483070226 0.830339122 0.209669489 0.589892647
#> [43] 0.561688013 0.046468886 0.955767731 0.736030248 0.287283034 0.970635903
#> [49] 0.236270363 0.184214255 0.156386009 0.682614109 0.522949452 0.561688013
#> [55] 0.502918165 0.963234809 0.114539990 0.933517415 0.383865124 0.018205258
#> [61] 0.870771263 0.599385288 0.700463895 0.838575580 0.473162582 0.502918165
#> [67] 0.097779148 0.262641333 0.062583277 0.404471071 0.655241447 0.753741048
#> [73] 0.332177775 0.682614109 0.894740830 0.608836602 0.664461479 0.353105298
#> [79] 0.933517415 0.727188276 0.796936538 0.918175637 0.788349086 0.320740370
#> [85] 0.771297085 0.970635903 0.985338174 0.287283034 0.933517415 0.762532488
#> [91] 0.170120398 0.894740830 0.627771771 0.813748746 0.424510182 0.985338174
#> [97] 0.275184997 0.822076527 0.646071755 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 79 96 123 187 108 39 45 55 166 194 49 63 140
#> 16.23 14.54 13.00 9.92 18.29 15.59 17.42 19.34 19.98 22.40 12.19 22.77 12.68
#> 55.1 61 39.1 5 26 78 183 197 128 168 10 32 92
#> 19.34 10.12 15.59 16.43 15.77 23.88 9.24 21.60 20.35 23.72 10.53 20.90 22.92
#> 108.1 49.1 55.2 170 76 66 49.2 150 24 179 36 134 179.1
#> 18.29 12.19 19.34 19.54 19.22 22.13 12.19 20.33 23.89 18.63 21.19 17.81 18.63
#> 42 66.1 171 45.1 86 77 133 36.1 91 136 194.1 15 125
#> 12.43 22.13 16.57 17.42 23.81 7.27 14.65 21.19 5.33 21.83 22.40 22.68 15.65
#> 108.2 45.2 8 25 92.1 70 158 78.1 107 130 6 56 97
#> 18.29 17.42 18.43 6.32 22.92 7.38 20.14 23.88 11.18 16.47 15.64 12.21 19.14
#> 8.1 129 139 168.1 170.1 100 57 32.1 125.1 101 85 26.1 128.1
#> 18.43 23.41 21.49 23.72 19.54 16.07 14.46 20.90 15.65 9.97 16.44 15.77 20.35
#> 70.1 29 140.1 183.1 14 90 123.1 91.1 127 36.2 70.2 13 169
#> 7.38 15.45 12.68 9.24 12.89 20.94 13.00 5.33 3.53 21.19 7.38 14.34 22.41
#> 101.1 79.1 154 55.3 127.1 153 37 188 161 165 94 53 19
#> 9.97 16.23 12.63 19.34 3.53 21.33 12.52 16.16 24.00 24.00 24.00 24.00 24.00
#> 116 174 62 38 122 2 142 162 186 132 94.1 103 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 182 162.1 95 137 74 122.1 178 146 126 196 2.1 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 94.2 98 163 178.1 142.2 146.1 7 95.1 182.1 62.1 75 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 185 72 147 102 172 95.2 173 46 62.2 122.2 146.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 80 144 87 7.1 112 112.1 141 176 75.1 22 12 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 75.2 160 1.1 75.3 71.1 120.1 163.2 172.1 103.1 120.2 54 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 119
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0003664853 0.6858825784 0.3879659856
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.03528633 0.02012735 0.11564359
#> grade_iii, Cure model
#> 0.83881911
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 110 17.56 1 65 0 1
#> 155 13.08 1 26 0 0
#> 199 19.81 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 154 12.63 1 20 1 0
#> 130 16.47 1 53 0 1
#> 36 21.19 1 48 0 1
#> 101 9.97 1 10 0 1
#> 110.1 17.56 1 65 0 1
#> 14 12.89 1 21 0 0
#> 166 19.98 1 48 0 0
#> 139 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 192 16.44 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 76 19.22 1 54 0 1
#> 150 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 128.1 20.35 1 35 0 1
#> 184 17.77 1 38 0 0
#> 24 23.89 1 38 0 0
#> 183 9.24 1 67 1 0
#> 24.1 23.89 1 38 0 0
#> 149.1 8.37 1 33 1 0
#> 105 19.75 1 60 0 0
#> 51 18.23 1 83 0 1
#> 179 18.63 1 42 0 0
#> 150.1 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 184.1 17.77 1 38 0 0
#> 56 12.21 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 133 14.65 1 57 0 0
#> 25 6.32 1 34 1 0
#> 164 23.60 1 76 0 1
#> 13 14.34 1 54 0 1
#> 159 10.55 1 50 0 1
#> 63 22.77 1 31 1 0
#> 169 22.41 1 46 0 0
#> 169.1 22.41 1 46 0 0
#> 36.2 21.19 1 48 0 1
#> 110.2 17.56 1 65 0 1
#> 60 13.15 1 38 1 0
#> 125 15.65 1 67 1 0
#> 18.1 15.21 1 49 1 0
#> 197 21.60 1 69 1 0
#> 177 12.53 1 75 0 0
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 180 14.82 1 37 0 0
#> 149.2 8.37 1 33 1 0
#> 113 22.86 1 34 0 0
#> 91 5.33 1 61 0 1
#> 96 14.54 1 33 0 1
#> 184.2 17.77 1 38 0 0
#> 51.1 18.23 1 83 0 1
#> 105.1 19.75 1 60 0 0
#> 52 10.42 1 52 0 1
#> 177.1 12.53 1 75 0 0
#> 153 21.33 1 55 1 0
#> 194 22.40 1 38 0 1
#> 171.1 16.57 1 41 0 1
#> 164.1 23.60 1 76 0 1
#> 99.1 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 149.3 8.37 1 33 1 0
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 18.2 15.21 1 49 1 0
#> 167.1 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 167.2 15.55 1 56 1 0
#> 130.1 16.47 1 53 0 1
#> 41 18.02 1 40 1 0
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 92 22.92 1 47 0 1
#> 57.1 14.46 1 45 0 1
#> 100 16.07 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 88 18.37 1 47 0 0
#> 169.2 22.41 1 46 0 0
#> 26 15.77 1 49 0 1
#> 96.1 14.54 1 33 0 1
#> 166.2 19.98 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 110.3 17.56 1 65 0 1
#> 130.2 16.47 1 53 0 1
#> 77.1 7.27 1 67 0 1
#> 63.1 22.77 1 31 1 0
#> 125.1 15.65 1 67 1 0
#> 177.2 12.53 1 75 0 0
#> 52.1 10.42 1 52 0 1
#> 52.2 10.42 1 52 0 1
#> 149.4 8.37 1 33 1 0
#> 63.2 22.77 1 31 1 0
#> 106 16.67 1 49 1 0
#> 26.1 15.77 1 49 0 1
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 81 14.06 1 34 0 0
#> 51.2 18.23 1 83 0 1
#> 57.2 14.46 1 45 0 1
#> 96.2 14.54 1 33 0 1
#> 154.1 12.63 1 20 1 0
#> 145 10.07 1 65 1 0
#> 20 24.00 0 46 1 0
#> 122 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 174 24.00 0 49 1 0
#> 74 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 2 24.00 0 9 0 0
#> 1 24.00 0 23 1 0
#> 102 24.00 0 49 0 0
#> 35.1 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 11 24.00 0 42 0 1
#> 198 24.00 0 66 0 1
#> 161 24.00 0 45 0 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 62 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 174.1 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 9.1 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 1.1 24.00 0 23 1 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 22.1 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 38.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 44 24.00 0 56 0 0
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 31.1 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 198.1 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 20.2 24.00 0 46 1 0
#> 94.1 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 71 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 122.1 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 71.2 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 103 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 83 24.00 0 6 0 0
#> 38.2 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 84.1 24.00 0 39 0 1
#> 31.2 24.00 0 36 0 1
#> 103.1 24.00 0 56 1 0
#> 121 24.00 0 57 1 0
#> 143.1 24.00 0 51 0 0
#> 143.2 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 27 24.00 0 63 1 0
#> 143.3 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 84.2 24.00 0 39 0 1
#> 53.1 24.00 0 32 0 1
#> 131 24.00 0 66 0 0
#> 9.2 24.00 0 31 1 0
#> 143.4 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 135.1 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.04 NA NA NA
#> 2 age, Cure model 0.0201 NA NA NA
#> 3 grade_ii, Cure model 0.116 NA NA NA
#> 4 grade_iii, Cure model 0.839 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000366 NA NA NA
#> 2 grade_ii, Survival model 0.686 NA NA NA
#> 3 grade_iii, Survival model 0.388 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03529 0.02013 0.11564 0.83882
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 256.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03528633 0.02012735 0.11564359 0.83881911
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0003664853 0.6858825784 0.3879659856
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.72008607 0.55036200 0.81919802 0.94502768 0.85340882 0.60981214
#> [7] 0.29520883 0.93218628 0.55036200 0.83303150 0.39245858 0.27178908
#> [13] 0.82614423 0.63432786 0.46868045 0.44970612 0.37321462 0.35395326
#> [19] 0.35395326 0.52375935 0.02548560 0.93862971 0.02548560 0.94502768
#> [25] 0.42093194 0.48764398 0.45919481 0.37321462 0.06832555 0.52375935
#> [31] 0.89313050 0.29520883 0.74884533 0.98780778 0.09489834 0.79823549
#> [37] 0.89973887 0.16909910 0.20763816 0.20763816 0.29520883 0.55036200
#> [43] 0.81225126 0.66670590 0.72008607 0.25926301 0.86668937 0.59301502
#> [49] 0.29520883 0.74160336 0.94502768 0.15051062 0.99391337 0.75608583
#> [55] 0.52375935 0.48764398 0.42093194 0.90632300 0.86668937 0.28374667
#> [61] 0.24607696 0.59301502 0.09489834 0.29520883 0.71261051 0.94502768
#> [67] 0.83991832 0.69017713 0.72008607 0.69017713 0.77730305 0.69017713
#> [73] 0.60981214 0.51473083 0.34391494 0.97555806 0.13189630 0.77730305
#> [79] 0.64249983 0.39245858 0.83991832 0.47816385 0.20763816 0.65066949
#> [85] 0.75608583 0.39245858 0.68235286 0.55036200 0.60981214 0.97555806
#> [91] 0.16909910 0.66670590 0.86668937 0.90632300 0.90632300 0.94502768
#> [97] 0.16909910 0.58443466 0.65066949 0.88652105 0.44011558 0.80524376
#> [103] 0.48764398 0.77730305 0.75608583 0.85340882 0.92572143 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 18 110 155 149 154 130 36 101 110.1 14 166 139 123
#> 15.21 17.56 13.08 8.37 12.63 16.47 21.19 9.97 17.56 12.89 19.98 21.49 13.00
#> 192 8 76 150 128 128.1 184 24 183 24.1 149.1 105 51
#> 16.44 18.43 19.22 20.33 20.35 20.35 17.77 23.89 9.24 23.89 8.37 19.75 18.23
#> 179 150.1 78 184.1 56 36.1 133 25 164 13 159 63 169
#> 18.63 20.33 23.88 17.77 12.21 21.19 14.65 6.32 23.60 14.34 10.55 22.77 22.41
#> 169.1 36.2 110.2 60 125 18.1 197 177 171 99 180 149.2 113
#> 22.41 21.19 17.56 13.15 15.65 15.21 21.60 12.53 16.57 21.19 14.82 8.37 22.86
#> 91 96 184.2 51.1 105.1 52 177.1 153 194 171.1 164.1 99.1 29
#> 5.33 14.54 17.77 18.23 19.75 10.42 12.53 21.33 22.40 16.57 23.60 21.19 15.45
#> 149.3 140 167 18.2 167.1 57 167.2 130.1 41 190 77 92 57.1
#> 8.37 12.68 15.55 15.21 15.55 14.46 15.55 16.47 18.02 20.81 7.27 22.92 14.46
#> 100 166.1 140.1 88 169.2 26 96.1 166.2 39 110.3 130.2 77.1 63.1
#> 16.07 19.98 12.68 18.37 22.41 15.77 14.54 19.98 15.59 17.56 16.47 7.27 22.77
#> 125.1 177.2 52.1 52.2 149.4 63.2 106 26.1 37 55 81 51.2 57.2
#> 15.65 12.53 10.42 10.42 8.37 22.77 16.67 15.77 12.52 19.34 14.06 18.23 14.46
#> 96.2 154.1 145 20 122 35 65 38 20.1 147 174 74 9
#> 14.54 12.63 10.07 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 98 2 1 102 35.1 74.1 75 54 11 198 161 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 62 22 174.1 132 9.1 2.1 151 1.1 143 21 31 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 94 38.1 173 53 44 82 84 31.1 178 198.1 160 20.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 34 44.1 185 161.1 71 162 122.1 71.1 118 186 71.2 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 135 83 38.2 148 84.1 31.2 103.1 121 143.1 143.2 11.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.3 137 84.2 53.1 131 9.2 143.4 7 176 64 132.1 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01417966 0.20432531 0.53078370
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.204541420 0.002551197 0.262431951
#> grade_iii, Cure model
#> 0.682512350
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 89 11.44 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 187 9.92 1 39 1 0
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 179 18.63 1 42 0 0
#> 37 12.52 1 57 1 0
#> 140 12.68 1 59 1 0
#> 170 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 8 18.43 1 32 0 0
#> 133 14.65 1 57 0 0
#> 16 8.71 1 71 0 1
#> 133.1 14.65 1 57 0 0
#> 81 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 110 17.56 1 65 0 1
#> 77 7.27 1 67 0 1
#> 23 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 52 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 26 15.77 1 49 0 1
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 113 22.86 1 34 0 0
#> 123 13.00 1 44 1 0
#> 175 21.91 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 133.2 14.65 1 57 0 0
#> 61 10.12 1 36 0 1
#> 52.1 10.42 1 52 0 1
#> 108 18.29 1 39 0 1
#> 50 10.02 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 26.1 15.77 1 49 0 1
#> 18 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 134 17.81 1 47 1 0
#> 23.1 16.92 1 61 0 0
#> 108.1 18.29 1 39 0 1
#> 93.1 10.33 1 52 0 1
#> 56 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 63.1 22.77 1 31 1 0
#> 154 12.63 1 20 1 0
#> 63.2 22.77 1 31 1 0
#> 91 5.33 1 61 0 1
#> 167 15.55 1 56 1 0
#> 4 17.64 1 NA 0 1
#> 179.1 18.63 1 42 0 0
#> 171 16.57 1 41 0 1
#> 10 10.53 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 18.1 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 190 20.81 1 42 1 0
#> 15.1 22.68 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 30 17.43 1 78 0 0
#> 81.1 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 93.2 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 171.1 16.57 1 41 0 1
#> 105 19.75 1 60 0 0
#> 130 16.47 1 53 0 1
#> 187.1 9.92 1 39 1 0
#> 40 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 167.1 15.55 1 56 1 0
#> 175.1 21.91 1 43 0 0
#> 125.2 15.65 1 67 1 0
#> 56.1 12.21 1 60 0 0
#> 117 17.46 1 26 0 1
#> 5 16.43 1 51 0 1
#> 130.1 16.47 1 53 0 1
#> 171.2 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 167.2 15.55 1 56 1 0
#> 177.1 12.53 1 75 0 0
#> 189 10.51 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 177.2 12.53 1 75 0 0
#> 157 15.10 1 47 0 0
#> 117.1 17.46 1 26 0 1
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 61.1 10.12 1 36 0 1
#> 153 21.33 1 55 1 0
#> 51.1 18.23 1 83 0 1
#> 139.1 21.49 1 63 1 0
#> 41 18.02 1 40 1 0
#> 79 16.23 1 54 1 0
#> 134.1 17.81 1 47 1 0
#> 30.1 17.43 1 78 0 0
#> 14 12.89 1 21 0 0
#> 91.1 5.33 1 61 0 1
#> 123.2 13.00 1 44 1 0
#> 97 19.14 1 65 0 1
#> 66 22.13 1 53 0 0
#> 41.1 18.02 1 40 1 0
#> 79.1 16.23 1 54 1 0
#> 140.2 12.68 1 59 1 0
#> 163 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 137 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 138 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 163.1 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 163.2 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 120 24.00 0 68 0 1
#> 165.1 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 2 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 7 24.00 0 37 1 0
#> 174.1 24.00 0 49 1 0
#> 135.1 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 38 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 146 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 72 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 94 24.00 0 51 0 1
#> 174.2 24.00 0 49 1 0
#> 67 24.00 0 25 0 0
#> 137.1 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 132.1 24.00 0 55 0 0
#> 12.1 24.00 0 63 0 0
#> 174.3 24.00 0 49 1 0
#> 64 24.00 0 43 0 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 119.1 24.00 0 17 0 0
#> 27 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 44.1 24.00 0 56 0 0
#> 80 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 54.1 24.00 0 53 1 0
#> 112 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 132.2 24.00 0 55 0 0
#> 34.1 24.00 0 36 0 0
#> 198.1 24.00 0 66 0 1
#> 98.1 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 80.1 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 33.1 24.00 0 53 0 0
#> 54.2 24.00 0 53 1 0
#> 27.1 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 174.4 24.00 0 49 1 0
#> 174.5 24.00 0 49 1 0
#> 53.1 24.00 0 32 0 1
#> 137.2 24.00 0 45 1 0
#> 132.3 24.00 0 55 0 0
#> 112.1 24.00 0 61 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.205 NA NA NA
#> 2 age, Cure model 0.00255 NA NA NA
#> 3 grade_ii, Cure model 0.262 NA NA NA
#> 4 grade_iii, Cure model 0.683 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0142 NA NA NA
#> 2 grade_ii, Survival model 0.204 NA NA NA
#> 3 grade_iii, Survival model 0.531 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.204541 0.002551 0.262432 0.682512
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 261 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.204541420 0.002551197 0.262431951 0.682512350
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01417966 0.20432531 0.53078370
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86620032 0.96693298 0.46258963 0.94759947 0.55702592 0.92301213
#> [7] 0.89313277 0.52474678 0.68824090 0.98193415 0.57676428 0.84322109
#> [13] 0.97453899 0.84322109 0.85703039 0.48862993 0.66708552 0.98562651
#> [19] 0.70817934 0.79975076 0.93955744 0.30347871 0.78939342 0.77323140
#> [25] 0.89313277 0.19818518 0.87533048 0.38435403 0.79975076 0.84322109
#> [31] 0.95925860 0.93955744 0.58662168 0.75066553 0.78939342 0.82902152
#> [37] 0.50114785 0.64458791 0.70817934 0.58662168 0.94759947 0.92719339
#> [43] 0.23456019 0.23456019 0.90609662 0.23456019 0.99290522 0.81461140
#> [49] 0.55702592 0.72095151 0.93543752 0.34500114 0.41877821 0.82902152
#> [55] 0.53584156 0.15718840 0.08770797 0.47582795 0.30347871 0.87533048
#> [61] 0.69508243 0.85703039 0.91042563 0.94759947 0.98927247 0.72095151
#> [67] 0.51312925 0.73904768 0.96693298 0.63678467 0.65959830 0.81461140
#> [73] 0.38435403 0.79975076 0.92719339 0.67430739 0.75646708 0.73904768
#> [79] 0.72095151 0.77869845 0.77869845 0.81461140 0.91042563 0.97453899
#> [85] 0.91042563 0.83849583 0.67430739 0.87077073 0.60497477 0.95925860
#> [91] 0.44835113 0.60497477 0.41877821 0.62111648 0.76215932 0.64458791
#> [97] 0.69508243 0.88867121 0.99290522 0.87533048 0.54676925 0.36527045
#> [103] 0.62111648 0.76215932 0.89313277 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 60 187 90 93 179 37 140 170 111 70 8 133 16
#> 13.15 9.92 20.94 10.33 18.63 12.52 12.68 19.54 17.45 7.38 18.43 14.65 8.71
#> 133.1 81 68 110 77 23 125 52 15 26 188 140.1 113
#> 14.65 14.06 20.62 17.56 7.27 16.92 15.65 10.42 22.68 15.77 16.16 12.68 22.86
#> 123 175 125.1 133.2 61 52.1 108 85 26.1 18 128 134 23.1
#> 13.00 21.91 15.65 14.65 10.12 10.42 18.29 16.44 15.77 15.21 20.35 17.81 16.92
#> 108.1 93.1 56 63 63.1 154 63.2 91 167 179.1 171 10 169
#> 18.29 10.33 12.21 22.77 22.77 12.63 22.77 5.33 15.55 18.63 16.57 10.53 22.41
#> 139 18.1 58 129 24 190 15.1 123.1 30 81.1 177 93.2 25
#> 21.49 15.21 19.34 23.41 23.89 20.81 22.68 13.00 17.43 14.06 12.53 10.33 6.32
#> 171.1 105 130 187.1 40 184 167.1 175.1 125.2 56.1 117 5 130.1
#> 16.57 19.75 16.47 9.92 18.00 17.77 15.55 21.91 15.65 12.21 17.46 16.43 16.47
#> 171.2 100 100.1 167.2 177.1 16.1 177.2 157 117.1 155 51 61.1 153
#> 16.57 16.07 16.07 15.55 12.53 8.71 12.53 15.10 17.46 13.08 18.23 10.12 21.33
#> 51.1 139.1 41 79 134.1 30.1 14 91.1 123.2 97 66 41.1 79.1
#> 18.23 21.49 18.02 16.23 17.81 17.43 12.89 5.33 13.00 19.14 22.13 18.02 16.23
#> 140.2 163 19 44 144 137 141 104 31 33 165 161 138
#> 12.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 156 163.1 132 174 53 163.2 84 120 165.1 186 2 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 135 87 116 7 174.1 135.1 142 54 38 116.1 116.2 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 151 72 198 65 109 182 94 174.2 67 137.1 193 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 174.3 64 46 200 119.1 27 35 200.1 44.1 80 131 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 54.1 112 22 132.2 34.1 198.1 98.1 173 80.1 147 83 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.2 27.1 126 148 174.4 174.5 53.1 137.2 132.3 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009709494 0.788748450 0.052260084
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.64086514 0.01411194 -0.22656555
#> grade_iii, Cure model
#> 0.71136882
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 187 9.92 1 39 1 0
#> 149 8.37 1 33 1 0
#> 52 10.42 1 52 0 1
#> 107 11.18 1 54 1 0
#> 51 18.23 1 83 0 1
#> 100 16.07 1 60 0 0
#> 60 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 37 12.52 1 57 1 0
#> 18 15.21 1 49 1 0
#> 184.1 17.77 1 38 0 0
#> 39 15.59 1 37 0 1
#> 187.1 9.92 1 39 1 0
#> 60.1 13.15 1 38 1 0
#> 100.1 16.07 1 60 0 0
#> 127 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 10 10.53 1 34 0 0
#> 8 18.43 1 32 0 0
#> 159 10.55 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 180 14.82 1 37 0 0
#> 10.1 10.53 1 34 0 0
#> 16 8.71 1 71 0 1
#> 91 5.33 1 61 0 1
#> 171 16.57 1 41 0 1
#> 14 12.89 1 21 0 0
#> 81.1 14.06 1 34 0 0
#> 70 7.38 1 30 1 0
#> 36 21.19 1 48 0 1
#> 23 16.92 1 61 0 0
#> 133.1 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 23.1 16.92 1 61 0 0
#> 37.1 12.52 1 57 1 0
#> 134 17.81 1 47 1 0
#> 18.1 15.21 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 69 23.23 1 25 0 1
#> 30 17.43 1 78 0 0
#> 170 19.54 1 43 0 1
#> 57 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 45 17.42 1 54 0 1
#> 125 15.65 1 67 1 0
#> 70.1 7.38 1 30 1 0
#> 92.1 22.92 1 47 0 1
#> 175 21.91 1 43 0 0
#> 66 22.13 1 53 0 0
#> 5 16.43 1 51 0 1
#> 60.2 13.15 1 38 1 0
#> 99 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 4.1 17.64 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 13 14.34 1 54 0 1
#> 111 17.45 1 47 0 1
#> 136 21.83 1 43 0 1
#> 63.1 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 189 10.51 1 NA 1 0
#> 14.2 12.89 1 21 0 0
#> 88 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 92.2 22.92 1 47 0 1
#> 30.1 17.43 1 78 0 0
#> 76.1 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 106 16.67 1 49 1 0
#> 168 23.72 1 70 0 0
#> 66.1 22.13 1 53 0 0
#> 5.1 16.43 1 51 0 1
#> 171.1 16.57 1 41 0 1
#> 159.1 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 90 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 59.1 10.16 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 99.1 21.19 1 38 0 1
#> 107.1 11.18 1 54 1 0
#> 145 10.07 1 65 1 0
#> 107.2 11.18 1 54 1 0
#> 107.3 11.18 1 54 1 0
#> 25 6.32 1 34 1 0
#> 26.1 15.77 1 49 0 1
#> 52.1 10.42 1 52 0 1
#> 125.1 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 69.1 23.23 1 25 0 1
#> 108 18.29 1 39 0 1
#> 189.1 10.51 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 18.2 15.21 1 49 1 0
#> 127.1 3.53 1 62 0 1
#> 99.2 21.19 1 38 0 1
#> 162 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 46 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 87 24.00 0 27 0 0
#> 47 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 198 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 142 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 47.1 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 156.1 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 28.1 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 174.1 24.00 0 49 1 0
#> 62 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 73.1 24.00 0 NA 0 1
#> 3 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 102 24.00 0 49 0 0
#> 54.1 24.00 0 53 1 0
#> 11 24.00 0 42 0 1
#> 182 24.00 0 35 0 0
#> 152 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 141 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 135.1 24.00 0 58 1 0
#> 80.1 24.00 0 41 0 0
#> 53.1 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 71 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 135.2 24.00 0 58 1 0
#> 87.1 24.00 0 27 0 0
#> 141.1 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 87.2 24.00 0 27 0 0
#> 72 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 48.1 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 80.2 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 135.3 24.00 0 58 1 0
#> 119.3 24.00 0 17 0 0
#> 102.1 24.00 0 49 0 0
#> 173 24.00 0 19 0 1
#> 53.2 24.00 0 32 0 1
#> 165.1 24.00 0 47 0 0
#> 47.2 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 17.1 24.00 0 38 0 1
#> 173.2 24.00 0 19 0 1
#> 186.1 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 146 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 28.2 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.641 NA NA NA
#> 2 age, Cure model 0.0141 NA NA NA
#> 3 grade_ii, Cure model -0.227 NA NA NA
#> 4 grade_iii, Cure model 0.711 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00971 NA NA NA
#> 2 grade_ii, Survival model 0.789 NA NA NA
#> 3 grade_iii, Survival model 0.0523 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64087 0.01411 -0.22657 0.71137
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 251.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64086514 0.01411194 -0.22656555 0.71136882
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009709494 0.788748450 0.052260084
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.54800993 0.19213745 0.78822783 0.95387341 0.96808871 0.93415109
#> [7] 0.89355976 0.52874182 0.69847447 0.83118796 0.66748852 0.87712073
#> [13] 0.76311307 0.54800993 0.74941054 0.95387341 0.83118796 0.69847447
#> [19] 0.99102910 0.30405432 0.92404762 0.49809955 0.91390075 0.27279045
#> [25] 0.81904601 0.66748852 0.78192742 0.92404762 0.96335957 0.98649546
#> [31] 0.63551578 0.84850891 0.81904601 0.97277139 0.38881917 0.61049570
#> [37] 0.78822783 0.46666115 0.37639417 0.61049570 0.87712073 0.53858887
#> [43] 0.76311307 0.71357678 0.13846919 0.58442279 0.44448055 0.80063231
#> [49] 0.65155805 0.60182781 0.72846000 0.97277139 0.19213745 0.34817711
#> [55] 0.31962240 0.68310952 0.83118796 0.38881917 0.05176687 0.45563297
#> [61] 0.74242518 0.81291669 0.56641029 0.36245021 0.27279045 0.84850891
#> [67] 0.84850891 0.50842931 0.48769114 0.19213745 0.58442279 0.46666115
#> [73] 0.65955363 0.80063231 0.88808917 0.62732502 0.10335843 0.31962240
#> [79] 0.68310952 0.63551578 0.91390075 0.86575027 0.25179433 0.43315780
#> [85] 0.75636290 0.86575027 0.38881917 0.89355976 0.94417373 0.89355976
#> [91] 0.89355976 0.98194288 0.71357678 0.93415109 0.72846000 0.56641029
#> [97] 0.13846919 0.51863913 0.94417373 0.76311307 0.99102910 0.38881917
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 184 92 133 187 149 52 107 51 100 60 85 37 18
#> 17.77 22.92 14.65 9.92 8.37 10.42 11.18 18.23 16.07 13.15 16.44 12.52 15.21
#> 184.1 39 187.1 60.1 100.1 127 15 10 8 159 63 81 85.1
#> 17.77 15.59 9.92 13.15 16.07 3.53 22.68 10.53 18.43 10.55 22.77 14.06 16.44
#> 180 10.1 16 91 171 14 81.1 70 36 23 133.1 76 197
#> 14.82 10.53 8.71 5.33 16.57 12.89 14.06 7.38 21.19 16.92 14.65 19.22 21.60
#> 23.1 37.1 134 18.1 26 69 30 170 57 130 45 125 70.1
#> 16.92 12.52 17.81 15.21 15.77 23.23 17.43 19.54 14.46 16.47 17.42 15.65 7.38
#> 92.1 175 66 5 60.2 99 24 58 6 13 111 136 63.1
#> 22.92 21.91 22.13 16.43 13.15 21.19 23.89 19.34 15.64 14.34 17.45 21.83 22.77
#> 14.1 14.2 88 97 92.2 30.1 76.1 181 57.1 43 106 168 66.1
#> 12.89 12.89 18.37 19.14 22.92 17.43 19.22 16.46 14.46 12.10 16.67 23.72 22.13
#> 5.1 171.1 159.1 177 113 90 29 177.1 99.1 107.1 145 107.2 107.3
#> 16.43 16.57 10.55 12.53 22.86 20.94 15.45 12.53 21.19 11.18 10.07 11.18 11.18
#> 25 26.1 52.1 125.1 111.1 69.1 108 145.1 18.2 127.1 99.2 162 200
#> 6.32 15.77 10.42 15.65 17.45 23.23 18.29 10.07 15.21 3.53 21.19 24.00 24.00
#> 46 12 87 47 118 174 198 138 119 142 80 67 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 47.1 48 17 156 198.1 156.1 186 53 28.1 174.1 62 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 3 54 163 119.1 147 84 94 102 54.1 11 182 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 22 64 141 135 135.1 80.1 53.1 112 71 12.1 135.2 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 131 87.2 72 165 71.1 119.2 82 48.1 82.1 80.2 137 135.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.3 102.1 173 53.2 165.1 47.2 173.1 65 104 103 17.1 173.2 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 146 151 28.2 178 19
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002722861 0.443798108 0.318619283
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.08453708 -0.01504077 0.67763612
#> grade_iii, Cure model
#> 2.23885638
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 181 16.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 153 21.33 1 55 1 0
#> 158 20.14 1 74 1 0
#> 183 9.24 1 67 1 0
#> 181.1 16.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 171.1 16.57 1 41 0 1
#> 37 12.52 1 57 1 0
#> 189 10.51 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 183.1 9.24 1 67 1 0
#> 59 10.16 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 81.1 14.06 1 34 0 0
#> 155 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 114 13.68 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 61 10.12 1 36 0 1
#> 70.1 7.38 1 30 1 0
#> 154 12.63 1 20 1 0
#> 192.1 16.44 1 31 1 0
#> 181.2 16.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 179 18.63 1 42 0 0
#> 157 15.10 1 47 0 0
#> 70.2 7.38 1 30 1 0
#> 42 12.43 1 49 0 1
#> 51 18.23 1 83 0 1
#> 15 22.68 1 48 0 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 81.2 14.06 1 34 0 0
#> 49 12.19 1 48 1 0
#> 192.2 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 70.3 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 14 12.89 1 21 0 0
#> 190.1 20.81 1 42 1 0
#> 88 18.37 1 47 0 0
#> 171.2 16.57 1 41 0 1
#> 14.1 12.89 1 21 0 0
#> 61.1 10.12 1 36 0 1
#> 96 14.54 1 33 0 1
#> 158.1 20.14 1 74 1 0
#> 133 14.65 1 57 0 0
#> 43.2 12.10 1 61 0 1
#> 129 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 26 15.77 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 36 21.19 1 48 0 1
#> 42.1 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 136.1 21.83 1 43 0 1
#> 129.1 23.41 1 53 1 0
#> 153.1 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 26.1 15.77 1 49 0 1
#> 91 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 157.1 15.10 1 47 0 0
#> 16 8.71 1 71 0 1
#> 99 21.19 1 38 0 1
#> 91.1 5.33 1 61 0 1
#> 149.1 8.37 1 33 1 0
#> 139 21.49 1 63 1 0
#> 187 9.92 1 39 1 0
#> 63 22.77 1 31 1 0
#> 110 17.56 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 168 23.72 1 70 0 0
#> 69.1 23.23 1 25 0 1
#> 18.1 15.21 1 49 1 0
#> 134 17.81 1 47 1 0
#> 183.2 9.24 1 67 1 0
#> 57 14.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 113 22.86 1 34 0 0
#> 125 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 61.2 10.12 1 36 0 1
#> 171.3 16.57 1 41 0 1
#> 15.1 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 70.4 7.38 1 30 1 0
#> 60.1 13.15 1 38 1 0
#> 5.1 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 179.1 18.63 1 42 0 0
#> 16.1 8.71 1 71 0 1
#> 15.2 22.68 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 16.2 8.71 1 71 0 1
#> 56 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 49.2 12.19 1 48 1 0
#> 175 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 131 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 65 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 118 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 35 24.00 0 51 0 0
#> 103.1 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 163 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 165.2 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 148.1 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 146.1 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 120 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 165.3 24.00 0 47 0 0
#> 2.1 24.00 0 9 0 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 148.2 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 174.1 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 118.1 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 131.1 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 131.2 24.00 0 66 0 0
#> 67.1 24.00 0 25 0 0
#> 21 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 62.1 24.00 0 71 0 0
#> 196.1 24.00 0 19 0 0
#> 174.2 24.00 0 49 1 0
#> 120.1 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 165.4 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 182.2 24.00 0 35 0 0
#> 20.1 24.00 0 46 1 0
#> 7 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 35.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 121 24.00 0 57 1 0
#> 160.2 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 12.1 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 38 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 9 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 84 24.00 0 39 0 1
#> 138 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0845 NA NA NA
#> 2 age, Cure model -0.0150 NA NA NA
#> 3 grade_ii, Cure model 0.678 NA NA NA
#> 4 grade_iii, Cure model 2.24 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00272 NA NA NA
#> 2 grade_ii, Survival model 0.444 NA NA NA
#> 3 grade_iii, Survival model 0.319 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.08454 -0.01504 0.67764 2.23886
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 237.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.08453708 -0.01504077 0.67763612 2.23885638
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002722861 0.443798108 0.318619283
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.83364174 0.44657173 0.41016957 0.22001676 0.29222281 0.87430292
#> [7] 0.44657173 0.47379769 0.41016957 0.73412495 0.34161418 0.87430292
#> [13] 0.65721158 0.72560642 0.92221587 0.63145751 0.93811096 0.63145751
#> [19] 0.67431281 0.26192992 0.54457660 0.84187541 0.93811096 0.71710633
#> [25] 0.47379769 0.44657173 0.73412495 0.31182355 0.57065916 0.93811096
#> [31] 0.75093345 0.35160011 0.12962294 0.80080432 0.80080432 0.63145751
#> [37] 0.77609192 0.47379769 0.36155862 0.93811096 0.55338367 0.69149752
#> [43] 0.26192992 0.33155870 0.41016957 0.69149752 0.84187541 0.60550944
#> [49] 0.29222281 0.59674436 0.80080432 0.04693961 0.17483548 0.51811077
#> [55] 0.77609192 0.24117602 0.75093345 0.58799775 0.17483548 0.04693961
#> [61] 0.22001676 0.40054676 0.01215214 0.51811077 0.97664227 0.07184231
#> [67] 0.70855800 0.57065916 0.89830202 0.24117602 0.97664227 0.92221587
#> [73] 0.20879236 0.86616153 0.11787333 0.38116376 0.60550944 0.02847592
#> [79] 0.07184231 0.55338367 0.37140922 0.87430292 0.62278515 0.28206253
#> [85] 0.09459746 0.53573473 0.50036406 0.84187541 0.41016957 0.12962294
#> [91] 0.99220021 0.93811096 0.65721158 0.50036406 0.68292584 0.31182355
#> [97] 0.89830202 0.12962294 0.09459746 0.89830202 0.76766576 0.39088049
#> [103] 0.19737611 0.77609192 0.16282102 0.82539176 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 159 181 171 153 158 183 181.1 192 171.1 37 108 183.1 60
#> 10.55 16.46 16.57 21.33 20.14 9.24 16.46 16.44 16.57 12.52 18.29 9.24 13.15
#> 177 149 81 70 81.1 155 190 39 61 70.1 154 192.1 181.2
#> 12.53 8.37 14.06 7.38 14.06 13.08 20.81 15.59 10.12 7.38 12.63 16.44 16.46
#> 37.1 179 157 70.2 42 51 15 43 43.1 81.2 49 192.2 41
#> 12.52 18.63 15.10 7.38 12.43 18.23 22.68 12.10 12.10 14.06 12.19 16.44 18.02
#> 70.3 18 14 190.1 88 171.2 14.1 61.1 96 158.1 133 43.2 129
#> 7.38 15.21 12.89 20.81 18.37 16.57 12.89 10.12 14.54 20.14 14.65 12.10 23.41
#> 136 26 49.1 36 42.1 180 136.1 129.1 153.1 45 86 26.1 91
#> 21.83 15.77 12.19 21.19 12.43 14.82 21.83 23.41 21.33 17.42 23.81 15.77 5.33
#> 69 140 157.1 16 99 91.1 149.1 139 187 63 110 96.1 168
#> 23.23 12.68 15.10 8.71 21.19 5.33 8.37 21.49 9.92 22.77 17.56 14.54 23.72
#> 69.1 18.1 134 183.2 57 128 113 125 5 61.2 171.3 15.1 127
#> 23.23 15.21 17.81 9.24 14.46 20.35 22.86 15.65 16.43 10.12 16.57 22.68 3.53
#> 70.4 60.1 5.1 123 179.1 16.1 15.2 113.1 16.2 56 111 197 49.2
#> 7.38 13.15 16.43 13.00 18.63 8.71 22.68 22.86 8.71 12.21 17.45 21.60 12.19
#> 175 107 131 148 102 174 165 146 156 27 162 75 65
#> 21.91 11.18 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 118 196 44 172 147 35 103.1 2 163 165.1 182 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 148.1 178 122 146.1 28 120 135 165.3 2.1 137 62 148.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 33 20 185 126 172.1 174.1 116 118.1 44.1 131.1 116.1 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 67.1 21 182.1 80 62.1 196.1 174.2 120.1 200 151 165.4 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 142 182.2 20.1 7 17 35.1 160 160.1 132 121 160.2 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 48 75.1 38 28.1 9 72 84 138 162.1 186 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001674849 0.510705567 -0.181238342
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.78391100 0.01238794 0.44547171
#> grade_iii, Cure model
#> 0.78632703
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 114 13.68 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 125 15.65 1 67 1 0
#> 107 11.18 1 54 1 0
#> 68 20.62 1 44 0 0
#> 97 19.14 1 65 0 1
#> 77 7.27 1 67 0 1
#> 179 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 153 21.33 1 55 1 0
#> 52 10.42 1 52 0 1
#> 166 19.98 1 48 0 0
#> 45 17.42 1 54 0 1
#> 192 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 69.1 23.23 1 25 0 1
#> 192.1 16.44 1 31 1 0
#> 105 19.75 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 90 20.94 1 50 0 1
#> 41 18.02 1 40 1 0
#> 171 16.57 1 41 0 1
#> 175 21.91 1 43 0 0
#> 166.1 19.98 1 48 0 0
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 79 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 167 15.55 1 56 1 0
#> 127 3.53 1 62 0 1
#> 85 16.44 1 36 0 0
#> 14.1 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 29 15.45 1 68 1 0
#> 150 20.33 1 48 0 0
#> 171.1 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 183 9.24 1 67 1 0
#> 133 14.65 1 57 0 0
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 50.1 10.02 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 76 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 15.1 22.68 1 48 0 0
#> 168 23.72 1 70 0 0
#> 140 12.68 1 59 1 0
#> 93 10.33 1 52 0 1
#> 88.1 18.37 1 47 0 0
#> 5 16.43 1 51 0 1
#> 106 16.67 1 49 1 0
#> 127.1 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 183.1 9.24 1 67 1 0
#> 149.1 8.37 1 33 1 0
#> 69.2 23.23 1 25 0 1
#> 55 19.34 1 69 0 1
#> 113 22.86 1 34 0 0
#> 153.1 21.33 1 55 1 0
#> 181 16.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 166.2 19.98 1 48 0 0
#> 128 20.35 1 35 0 1
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 14.2 12.89 1 21 0 0
#> 179.1 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 49 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 114.1 13.68 1 NA 0 0
#> 59.1 10.16 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 91 5.33 1 61 0 1
#> 14.3 12.89 1 21 0 0
#> 81 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 145.1 10.07 1 65 1 0
#> 180 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 192.2 16.44 1 31 1 0
#> 190 20.81 1 42 1 0
#> 90.1 20.94 1 50 0 1
#> 86.1 23.81 1 58 0 1
#> 192.3 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 42 12.43 1 49 0 1
#> 150.1 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 114.2 13.68 1 NA 0 0
#> 79.1 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 153.2 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 18 15.21 1 49 1 0
#> 145.2 10.07 1 65 1 0
#> 150.2 20.33 1 48 0 0
#> 110 17.56 1 65 0 1
#> 55.1 19.34 1 69 0 1
#> 88.2 18.37 1 47 0 0
#> 3 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 193 24.00 0 45 0 1
#> 7 24.00 0 37 1 0
#> 115 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 53 24.00 0 32 0 1
#> 120 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 71 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 116 24.00 0 58 0 1
#> 142 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 54.1 24.00 0 53 1 0
#> 120.1 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 193.1 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 120.2 24.00 0 68 0 1
#> 119.1 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 176 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 138.1 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 35.1 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 120.3 24.00 0 68 0 1
#> 38 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 137.1 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 72.1 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 131 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 75.1 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 176.2 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 143.1 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 115.1 24.00 0 NA 1 0
#> 163 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 48 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 172.1 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 151 24.00 0 42 0 0
#> 67.1 24.00 0 25 0 0
#> 119.2 24.00 0 17 0 0
#> 112.1 24.00 0 61 0 0
#> 122.1 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 62.2 24.00 0 71 0 0
#> 200.1 24.00 0 64 0 0
#> 31 24.00 0 36 0 1
#> 138.2 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 44 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.784 NA NA NA
#> 2 age, Cure model 0.0124 NA NA NA
#> 3 grade_ii, Cure model 0.445 NA NA NA
#> 4 grade_iii, Cure model 0.786 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00167 NA NA NA
#> 2 grade_ii, Survival model 0.511 NA NA NA
#> 3 grade_iii, Survival model -0.181 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.78391 0.01239 0.44547 0.78633
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 252.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.78391100 0.01238794 0.44547171 0.78632703
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001674849 0.510705567 -0.181238342
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86622425 0.69751601 0.87445011 0.29603852 0.42521414 0.96913316
#> [7] 0.43517566 0.06178110 0.21356618 0.89057559 0.35674002 0.56088431
#> [13] 0.61788698 0.45480608 0.06178110 0.61788698 0.38575795 0.87445011
#> [19] 0.68865699 0.26468096 0.49364628 0.58954237 0.17599844 0.35674002
#> [25] 0.13893582 0.80022471 0.90679456 0.67102910 0.75786384 0.71505390
#> [31] 0.98458561 0.61788698 0.80022471 0.51293657 0.95375505 0.09787592
#> [37] 0.72374045 0.31678729 0.58954237 0.79185250 0.93037752 0.74936359
#> [43] 0.12600536 0.34672290 0.01150357 0.41526890 0.55129213 0.13893582
#> [49] 0.03413733 0.83314328 0.89868178 0.45480608 0.66195881 0.58007983
#> [55] 0.98458561 0.48378037 0.93037752 0.95375505 0.06178110 0.39565690
#> [61] 0.11199115 0.21356618 0.60837947 0.50336040 0.35674002 0.30639262
#> [67] 0.53207770 0.16324443 0.80022471 0.43517566 0.84972043 0.24385929
#> [73] 0.54167661 0.04784081 0.85800432 0.78340942 0.24385929 0.97685706
#> [79] 0.80022471 0.77489515 0.57049075 0.90679456 0.74085367 0.18868423
#> [85] 0.61788698 0.28565669 0.26468096 0.01150357 0.61788698 0.20145918
#> [91] 0.84142800 0.31678729 0.76637538 0.67102910 0.70627883 0.21356618
#> [97] 0.94593843 0.73233750 0.90679456 0.31678729 0.52250101 0.39565690
#> [103] 0.45480608 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 43 125 107 68 97 77 179 69 153 52 166 45 192
#> 12.10 15.65 11.18 20.62 19.14 7.27 18.63 23.23 21.33 10.42 19.98 17.42 16.44
#> 88 69.1 192.1 105 107.1 100 90 41 171 175 166.1 15 14
#> 18.37 23.23 16.44 19.75 11.18 16.07 20.94 18.02 16.57 21.91 19.98 22.68 12.89
#> 145 79 96 167 127 85 14.1 184 149 92 29 150 171.1
#> 10.07 16.23 14.54 15.55 3.53 16.44 12.89 17.77 8.37 22.92 15.45 20.33 16.57
#> 123 183 133 63 158 86 76 30 15.1 168 140 93 88.1
#> 13.00 9.24 14.65 22.77 20.14 23.81 19.22 17.43 22.68 23.72 12.68 10.33 18.37
#> 5 106 127.1 51 183.1 149.1 69.2 55 113 153.1 181 40 166.2
#> 16.43 16.67 3.53 18.23 9.24 8.37 23.23 19.34 22.86 21.33 16.46 18.00 19.98
#> 128 117 194 14.2 179.1 56 99 111 164 49 60 36 91
#> 20.35 17.46 22.40 12.89 18.63 12.21 21.19 17.45 23.60 12.19 13.15 21.19 5.33
#> 14.3 81 23 145.1 180 136 192.2 190 90.1 86.1 192.3 197 42
#> 12.89 14.06 16.92 10.07 14.82 21.83 16.44 20.81 20.94 23.81 16.44 21.60 12.43
#> 150.1 13 79.1 39 153.2 16 18 145.2 150.2 110 55.1 88.2 3
#> 20.33 14.34 16.23 15.59 21.33 8.71 15.21 10.07 20.33 17.56 19.34 18.37 24.00
#> 2 193 7 138 94 53 120 137 54 185 119 141 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 62 121 21 12 71 103 116 142 172 67 54.1 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 112 20 156 193.1 174 120.2 119.1 82 200 176 35 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 161 165 35.1 9 120.3 38 176.1 137.1 84 72.1 148 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 7.1 75.1 143 47 176.2 116.1 102 143.1 3.1 163 47.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 182 172.1 103.1 132 151 67.1 119.2 112.1 122.1 38.1 62.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 200.1 31 138.2 11 44
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002255654 0.466698726 0.213462341
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.149632934 0.002440683 -0.114186944
#> grade_iii, Cure model
#> 0.541750560
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 124 9.73 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 23 16.92 1 61 0 0
#> 124.1 9.73 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 30 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 8 18.43 1 32 0 0
#> 51 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 194 22.40 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 69 23.23 1 25 0 1
#> 179 18.63 1 42 0 0
#> 32 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 40.1 18.00 1 28 1 0
#> 66 22.13 1 53 0 0
#> 194.1 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 40.2 18.00 1 28 1 0
#> 37 12.52 1 57 1 0
#> 101 9.97 1 10 0 1
#> 106 16.67 1 49 1 0
#> 128.1 20.35 1 35 0 1
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 6 15.64 1 39 0 0
#> 79 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 97.1 19.14 1 65 0 1
#> 140 12.68 1 59 1 0
#> 90.1 20.94 1 50 0 1
#> 170 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 134 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 101.1 9.97 1 10 0 1
#> 66.1 22.13 1 53 0 0
#> 125 15.65 1 67 1 0
#> 39 15.59 1 37 0 1
#> 18 15.21 1 49 1 0
#> 69.1 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 105 19.75 1 60 0 0
#> 66.2 22.13 1 53 0 0
#> 88 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 171 16.57 1 41 0 1
#> 140.1 12.68 1 59 1 0
#> 117 17.46 1 26 0 1
#> 145.1 10.07 1 65 1 0
#> 101.2 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 18.1 15.21 1 49 1 0
#> 188.2 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 188.3 16.16 1 46 0 1
#> 88.1 18.37 1 47 0 0
#> 81 14.06 1 34 0 0
#> 10 10.53 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 15 22.68 1 48 0 0
#> 192 16.44 1 31 1 0
#> 18.2 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 25 6.32 1 34 1 0
#> 30.1 17.43 1 78 0 0
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 5 16.43 1 51 0 1
#> 59.1 10.16 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 40.3 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 91 5.33 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 78.1 23.88 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 189.1 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 150.1 20.33 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 164.1 23.60 1 76 0 1
#> 50 10.02 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 140.2 12.68 1 59 1 0
#> 50.1 10.02 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 189.2 10.51 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 181.1 16.46 1 45 0 1
#> 139.1 21.49 1 63 1 0
#> 184 17.77 1 38 0 0
#> 134.1 17.81 1 47 1 0
#> 172 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 118 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 182 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 193.1 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 3.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 120 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 161 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 62.1 24.00 0 71 0 0
#> 193.2 24.00 0 45 0 1
#> 7 24.00 0 37 1 0
#> 119 24.00 0 17 0 0
#> 7.1 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 47 24.00 0 38 0 1
#> 137.1 24.00 0 45 1 0
#> 84.1 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 146.1 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 94 24.00 0 51 0 1
#> 135.1 24.00 0 58 1 0
#> 142.1 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 115 24.00 0 NA 1 0
#> 142.2 24.00 0 53 0 0
#> 62.2 24.00 0 71 0 0
#> 104.1 24.00 0 50 1 0
#> 109.1 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 21.1 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 11.1 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 34 24.00 0 36 0 0
#> 19.1 24.00 0 57 0 1
#> 47.1 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 47.2 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 193.3 24.00 0 45 0 1
#> 172.2 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 27.1 24.00 0 63 1 0
#> 116.2 24.00 0 58 0 1
#> 163.1 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 67.1 24.00 0 25 0 0
#> 104.2 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.150 NA NA NA
#> 2 age, Cure model 0.00244 NA NA NA
#> 3 grade_ii, Cure model -0.114 NA NA NA
#> 4 grade_iii, Cure model 0.542 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00226 NA NA NA
#> 2 grade_ii, Survival model 0.467 NA NA NA
#> 3 grade_iii, Survival model 0.213 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.149633 0.002441 -0.114187 0.541751
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 253.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.149632934 0.002440683 -0.114186944 0.541750560
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002255654 0.466698726 0.213462341
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.51324217 0.27353587 0.63061609 0.32972846 0.60400269 0.72474567
#> [7] 0.68272889 0.41387585 0.46362011 0.50333406 0.85932647 0.18529437
#> [13] 0.72474567 0.12688026 0.43399514 0.31869147 0.81293843 0.51324217
#> [19] 0.21157062 0.18529437 0.29644469 0.10985359 0.91241958 0.51324217
#> [25] 0.87457973 0.93467053 0.63947771 0.32972846 0.89734252 0.66564792
#> [31] 0.77332482 0.71639711 0.43399514 0.75702197 0.41387585 0.83647399
#> [37] 0.29644469 0.39332381 0.96387104 0.54982633 0.91992459 0.99282539
#> [43] 0.15640707 0.03004449 0.93467053 0.21157062 0.76521051 0.78143131
#> [49] 0.78950883 0.12688026 0.62173607 0.97115245 0.38270537 0.21157062
#> [55] 0.48352263 0.35095898 0.43399514 0.64824445 0.83647399 0.57708569
#> [61] 0.91992459 0.93467053 0.78950883 0.72474567 0.07445846 0.72474567
#> [67] 0.48352263 0.82860784 0.88976669 0.39332381 0.17092010 0.68272889
#> [73] 0.78950883 0.24889993 0.97840992 0.60400269 0.65696895 0.90489336
#> [79] 0.88218572 0.69964174 0.57708569 0.51324217 0.95656463 0.98562874
#> [85] 0.85932647 0.03004449 0.24889993 0.59501886 0.35095898 0.46362011
#> [91] 0.07445846 0.81293843 0.83647399 0.37204409 0.69964174 0.66564792
#> [97] 0.27353587 0.56795897 0.54982633 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 40 139 23 128 30 188 85 97 8 51 177 194 188.1
#> 18.00 21.49 16.92 20.35 17.43 16.16 16.44 19.14 18.43 18.23 12.53 22.40 16.16
#> 69 179 32 180 40.1 66 194.1 90 129 61 40.2 37 101
#> 23.23 18.63 20.90 14.82 18.00 22.13 22.40 20.94 23.41 10.12 18.00 12.52 9.97
#> 106 128.1 52 181 6 79 179.1 100 97.1 140 90.1 170 16
#> 16.67 20.35 10.42 16.46 15.64 16.23 18.63 16.07 19.14 12.68 20.94 19.54 8.71
#> 134 145 127 63 78 101.1 66.1 125 39 18 69.1 45 77
#> 17.81 10.07 3.53 22.77 23.88 9.97 22.13 15.65 15.59 15.21 23.23 17.42 7.27
#> 105 66.2 88 150 179.2 171 140.1 117 145.1 101.2 18.1 188.2 164
#> 19.75 22.13 18.37 20.33 18.63 16.57 12.68 17.46 10.07 9.97 15.21 16.16 23.60
#> 188.3 88.1 81 10 170.1 15 192 18.2 136 25 30.1 130 93
#> 16.16 18.37 14.06 10.53 19.54 22.68 16.44 15.21 21.83 6.32 17.43 16.47 10.33
#> 42 5 117.1 40.3 183 91 177.1 78.1 136.1 111 150.1 8.1 164.1
#> 12.43 16.43 17.46 18.00 9.24 5.33 12.53 23.88 21.83 17.45 20.33 18.43 23.60
#> 180.1 140.2 166 5.1 181.1 139.1 184 134.1 172 160 84 98 122
#> 14.82 12.68 19.98 16.43 16.46 21.49 17.77 17.81 24.00 24.00 24.00 24.00 24.00
#> 135 146 116 118 172.1 31 3 193 182 103 193.1 67 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 3.1 71 17 82 120 19 87 176 65 38 109 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 161 64 62.1 193.2 7 119 7.1 142 147 47 137.1 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 21 148 152 146.1 80 173 94 135.1 142.1 94.1 11 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 104.1 109.1 103.1 21.1 27 11.1 163 2 34 19.1 47.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 47.2 20 185 147.1 193.3 172.2 74 27.1 116.2 163.1 72 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.2 46 35 54
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02026082 0.56877995 0.25512911
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.99875020 0.01547455 0.29847786
#> grade_iii, Cure model
#> 1.05651440
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 14 12.89 1 21 0 0
#> 88 18.37 1 47 0 0
#> 93 10.33 1 52 0 1
#> 90 20.94 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 189 10.51 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 184 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 40 18.00 1 28 1 0
#> 41 18.02 1 40 1 0
#> 158.1 20.14 1 74 1 0
#> 4 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 63 22.77 1 31 1 0
#> 66 22.13 1 53 0 0
#> 52 10.42 1 52 0 1
#> 25 6.32 1 34 1 0
#> 189.1 10.51 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 97 19.14 1 65 0 1
#> 117 17.46 1 26 0 1
#> 66.1 22.13 1 53 0 0
#> 114 13.68 1 NA 0 0
#> 60.1 13.15 1 38 1 0
#> 68 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 96.1 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 58 19.34 1 39 0 0
#> 88.1 18.37 1 47 0 0
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 15.1 22.68 1 48 0 0
#> 70 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 136 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 88.2 18.37 1 47 0 0
#> 89.1 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 57 14.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 183 9.24 1 67 1 0
#> 124.1 9.73 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 111.1 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 55 19.34 1 69 0 1
#> 124.2 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 128 20.35 1 35 0 1
#> 79 16.23 1 54 1 0
#> 139 21.49 1 63 1 0
#> 179 18.63 1 42 0 0
#> 158.2 20.14 1 74 1 0
#> 153 21.33 1 55 1 0
#> 29 15.45 1 68 1 0
#> 125.1 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 136.1 21.83 1 43 0 1
#> 113 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 124.3 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 129 23.41 1 53 1 0
#> 85.1 16.44 1 36 0 0
#> 92 22.92 1 47 0 1
#> 88.3 18.37 1 47 0 0
#> 129.1 23.41 1 53 1 0
#> 6 15.64 1 39 0 0
#> 26 15.77 1 49 0 1
#> 10 10.53 1 34 0 0
#> 136.2 21.83 1 43 0 1
#> 134 17.81 1 47 1 0
#> 4.1 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 51 18.23 1 83 0 1
#> 166.1 19.98 1 48 0 0
#> 180 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 123.1 13.00 1 44 1 0
#> 18 15.21 1 49 1 0
#> 181.1 16.46 1 45 0 1
#> 18.1 15.21 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 114.1 13.68 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 23 16.92 1 61 0 0
#> 86.1 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 129.2 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 30 17.43 1 78 0 0
#> 15.2 22.68 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 57.1 14.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 154 12.63 1 20 1 0
#> 50 10.02 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 167 15.55 1 56 1 0
#> 46 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 163 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 53 24.00 0 32 0 1
#> 20 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 104.1 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 138.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 34 24.00 0 36 0 0
#> 94 24.00 0 51 0 1
#> 118 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 38 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 112 24.00 0 61 0 0
#> 118.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 17 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 103 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#> 118.2 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 138.2 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 131.1 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 119.1 24.00 0 17 0 0
#> 104.2 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 196.1 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 21.1 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 196.2 24.00 0 19 0 0
#> 162 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 146.1 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 196.3 24.00 0 19 0 0
#> 173.1 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 53.1 24.00 0 32 0 1
#> 112.1 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 151.1 24.00 0 42 0 0
#> 172.1 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 21.2 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 141.1 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 122.1 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 118.3 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 7.1 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.999 NA NA NA
#> 2 age, Cure model 0.0155 NA NA NA
#> 3 grade_ii, Cure model 0.298 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0203 NA NA NA
#> 2 grade_ii, Survival model 0.569 NA NA NA
#> 3 grade_iii, Survival model 0.255 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99875 0.01547 0.29848 1.05651
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99875020 0.01547455 0.29847786 1.05651440
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02026082 0.56877995 0.25512911
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 4.337781e-01 7.287571e-01 1.405478e-01 8.507836e-01 6.426067e-02
#> [6] 5.474145e-02 8.036551e-02 2.108750e-01 1.642134e-02 1.920422e-01
#> [11] 1.826954e-01 8.036551e-02 6.295061e-01 1.409687e-02 2.426150e-02
#> [16] 8.151461e-01 9.435149e-01 8.151461e-01 3.931326e-01 1.251675e-01
#> [21] 2.306064e-01 2.426150e-02 6.295061e-01 6.942233e-02 5.353607e-01
#> [26] 5.353607e-01 3.064542e-01 4.160237e-02 1.110404e-01 1.405478e-01
#> [31] 6.619979e-01 9.435149e-01 2.407209e-01 1.642134e-02 9.247208e-01
#> [36] 6.911648e-04 3.081034e-02 6.951564e-01 1.405478e-01 1.630743e-05
#> [41] 5.658288e-01 3.300880e-01 9.059414e-01 7.629617e-01 2.407209e-01
#> [46] 9.793717e-02 1.110404e-01 2.948404e-01 7.482087e-02 3.546321e-01
#> [51] 4.579018e-02 1.327300e-01 8.036551e-02 5.018184e-02 4.761307e-01
#> [56] 3.931326e-01 8.690051e-01 3.081034e-02 1.179506e-02 2.834769e-01
#> [61] 5.971080e-01 3.567810e-03 3.300880e-01 9.697633e-03 1.405478e-01
#> [66] 3.567810e-03 4.199188e-01 3.673066e-01 7.975560e-01 3.081034e-02
#> [71] 2.013885e-01 2.205964e-01 6.132005e-01 3.673066e-01 1.734502e-01
#> [76] 9.793717e-02 5.202001e-01 1.413437e-04 6.951564e-01 4.907667e-01
#> [81] 3.064542e-01 4.907667e-01 6.619979e-01 9.808956e-01 2.722687e-01
#> [86] 1.413437e-04 5.474145e-02 3.567810e-03 2.175312e-03 2.613785e-01
#> [91] 1.642134e-02 4.337781e-01 5.658288e-01 6.911648e-04 8.873720e-01
#> [96] 7.458942e-01 7.801570e-01 7.806269e-03 4.617401e-01 0.000000e+00
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 39 14 88 93 90 36 158 184 15 40 41 158.1 60
#> 15.59 12.89 18.37 10.33 20.94 21.19 20.14 17.77 22.68 18.00 18.02 20.14 13.15
#> 63 66 52 25 52.1 125 97 117 66.1 60.1 68 96 96.1
#> 22.77 22.13 10.42 6.32 10.42 15.65 19.14 17.46 22.13 13.15 20.62 14.54 14.54
#> 181 197 58 88.1 155 25.1 111 15.1 70 168 136 123 88.2
#> 16.46 21.60 19.34 18.37 13.08 6.32 17.45 22.68 7.38 23.72 21.83 13.00 18.37
#> 24 57 85 183 49 111.1 166 55 130 128 79 139 179
#> 23.89 14.46 16.44 9.24 12.19 17.45 19.98 19.34 16.47 20.35 16.23 21.49 18.63
#> 158.2 153 29 125.1 61 136.1 113 106 13 129 85.1 92 88.3
#> 20.14 21.33 15.45 15.65 10.12 21.83 22.86 16.67 14.34 23.41 16.44 22.92 18.37
#> 129.1 6 26 10 136.2 134 110 81 26.1 51 166.1 180 86
#> 23.41 15.64 15.77 10.53 21.83 17.81 17.56 14.06 15.77 18.23 19.98 14.82 23.81
#> 123.1 18 181.1 18.1 155.1 127 23 86.1 36.1 129.2 164 30 15.2
#> 13.00 15.21 16.46 15.21 13.08 3.53 16.92 23.81 21.19 23.41 23.60 17.43 22.68
#> 39.1 57.1 168.1 145 154 159 69 167 46 119 163 35 141
#> 15.59 14.46 23.72 10.07 12.63 10.55 23.23 15.55 24.00 24.00 24.00 24.00 24.00
#> 84 53 20 104 54 7 182 196 83 31 138 126 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 72 120 104.1 12 135 138.1 151 34 94 118 132 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 82 112 118.1 178 173 131 172 165 161 17 132.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 118.2 146 138.2 176 131.1 165.1 119.1 104.2 176.1 64 196.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 21.1 198 196.2 162 31.1 146.1 186 196.3 173.1 67 53.1 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 198.1 151.1 172.1 65 21.2 122 1 141.1 87 122.1 48 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 118.3 103.1 7.1 80
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004713134 0.861160710 0.285250391
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93449280 0.01974741 -0.54299212
#> grade_iii, Cure model
#> 0.97751579
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 55 19.34 1 69 0 1
#> 32 20.90 1 37 1 0
#> 88 18.37 1 47 0 0
#> 76 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 4 17.64 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 57 14.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 50 10.02 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 77 7.27 1 67 0 1
#> 4.1 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 50.2 10.02 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 136.1 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 68.1 20.62 1 44 0 0
#> 106 16.67 1 49 1 0
#> 86 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 133 14.65 1 57 0 0
#> 58 19.34 1 39 0 0
#> 58.1 19.34 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 37 12.52 1 57 1 0
#> 117 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 192 16.44 1 31 1 0
#> 90 20.94 1 50 0 1
#> 45 17.42 1 54 0 1
#> 171 16.57 1 41 0 1
#> 92 22.92 1 47 0 1
#> 37.1 12.52 1 57 1 0
#> 171.1 16.57 1 41 0 1
#> 110.1 17.56 1 65 0 1
#> 136.2 21.83 1 43 0 1
#> 170 19.54 1 43 0 1
#> 194 22.40 1 38 0 1
#> 175 21.91 1 43 0 0
#> 77.1 7.27 1 67 0 1
#> 168 23.72 1 70 0 0
#> 107 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 66 22.13 1 53 0 0
#> 113 22.86 1 34 0 0
#> 167 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 18 15.21 1 49 1 0
#> 107.1 11.18 1 54 1 0
#> 169 22.41 1 46 0 0
#> 52 10.42 1 52 0 1
#> 123.1 13.00 1 44 1 0
#> 197 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 61 10.12 1 36 0 1
#> 14 12.89 1 21 0 0
#> 92.1 22.92 1 47 0 1
#> 85.1 16.44 1 36 0 0
#> 130.2 16.47 1 53 0 1
#> 183 9.24 1 67 1 0
#> 194.1 22.40 1 38 0 1
#> 26 15.77 1 49 0 1
#> 155 13.08 1 26 0 0
#> 18.1 15.21 1 49 1 0
#> 100 16.07 1 60 0 0
#> 184 17.77 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 108.1 18.29 1 39 0 1
#> 50.3 10.02 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 171.2 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 105 19.75 1 60 0 0
#> 24 23.89 1 38 0 0
#> 189.1 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 86.2 23.81 1 58 0 1
#> 189.2 10.51 1 NA 1 0
#> 189.3 10.51 1 NA 1 0
#> 130.3 16.47 1 53 0 1
#> 117.1 17.46 1 26 0 1
#> 133.1 14.65 1 57 0 0
#> 153 21.33 1 55 1 0
#> 194.2 22.40 1 38 0 1
#> 134 17.81 1 47 1 0
#> 78 23.88 1 43 0 0
#> 111.1 17.45 1 47 0 1
#> 23.1 16.92 1 61 0 0
#> 129 23.41 1 53 1 0
#> 110.2 17.56 1 65 0 1
#> 57.1 14.46 1 45 0 1
#> 90.1 20.94 1 50 0 1
#> 78.1 23.88 1 43 0 0
#> 128.1 20.35 1 35 0 1
#> 60 13.15 1 38 1 0
#> 194.3 22.40 1 38 0 1
#> 30 17.43 1 78 0 0
#> 113.1 22.86 1 34 0 0
#> 175.1 21.91 1 43 0 0
#> 155.1 13.08 1 26 0 0
#> 15 22.68 1 48 0 0
#> 19 24.00 0 57 0 1
#> 12 24.00 0 63 0 0
#> 73 24.00 0 NA 0 1
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 191 24.00 0 60 0 1
#> 176 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 64 24.00 0 43 0 0
#> 104.1 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 173 24.00 0 19 0 1
#> 152 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 118.1 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 172.2 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 12.1 24.00 0 63 0 0
#> 186 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 65.1 24.00 0 57 1 0
#> 118.2 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 33.1 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 148.1 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 173.1 24.00 0 19 0 1
#> 84 24.00 0 39 0 1
#> 118.3 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 31.2 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 122.2 24.00 0 66 0 0
#> 173.2 24.00 0 19 0 1
#> 80 24.00 0 41 0 0
#> 12.2 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 144.1 24.00 0 28 0 1
#> 146.1 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 109.1 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 2 24.00 0 9 0 0
#> 47.1 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 172.3 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 80.1 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 172.4 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 138.1 24.00 0 44 1 0
#> 172.5 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.934 NA NA NA
#> 2 age, Cure model 0.0197 NA NA NA
#> 3 grade_ii, Cure model -0.543 NA NA NA
#> 4 grade_iii, Cure model 0.978 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00471 NA NA NA
#> 2 grade_ii, Survival model 0.861 NA NA NA
#> 3 grade_iii, Survival model 0.285 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93449 0.01975 -0.54299 0.97752
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 241.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93449280 0.01974741 -0.54299212 0.97751579
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004713134 0.861160710 0.285250391
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.859512011 0.518984534 0.420816396 0.341818415 0.469773994 0.449920671
#> [7] 0.391295194 0.247176595 0.663592172 0.663592172 0.813575056 0.710858607
#> [13] 0.351770242 0.982847515 0.895451570 0.605889861 0.247176595 0.922036143
#> [19] 0.351770242 0.625387706 0.042253467 0.371599750 0.795088696 0.420816396
#> [25] 0.420816396 0.042253467 0.904436615 0.547844372 0.479757647 0.710858607
#> [31] 0.321632937 0.596140281 0.635080116 0.096860959 0.904436615 0.635080116
#> [37] 0.518984534 0.247176595 0.410969743 0.162422818 0.224868020 0.982847515
#> [43] 0.072867663 0.930873576 0.459832329 0.202959599 0.117846495 0.758062435
#> [49] 0.965573081 0.767492090 0.930873576 0.150830468 0.948191530 0.859512011
#> [55] 0.279511180 0.886493290 0.956887141 0.877462777 0.096860959 0.710858607
#> [61] 0.663592172 0.974238066 0.162422818 0.748535959 0.841208517 0.767492090
#> [67] 0.739002714 0.509192282 0.701256652 0.311343526 0.202959599 0.479757647
#> [73] 0.290423377 0.635080116 0.567136560 0.401102750 0.005683369 0.785842111
#> [79] 0.042253467 0.663592172 0.547844372 0.795088696 0.301033433 0.162422818
#> [85] 0.499430816 0.018796741 0.567136560 0.605889861 0.085568196 0.518984534
#> [91] 0.813575056 0.321632937 0.018796741 0.371599750 0.832029607 0.162422818
#> [97] 0.586385724 0.117846495 0.224868020 0.841208517 0.139409550 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 123 110 55 32 88 76 158 136 130 130.1 57 85 68
#> 13.00 17.56 19.34 20.90 18.37 19.22 20.14 21.83 16.47 16.47 14.46 16.44 20.62
#> 77 177 23 136.1 42 68.1 106 86 128 133 58 58.1 86.1
#> 7.27 12.53 16.92 21.83 12.43 20.62 16.67 23.81 20.35 14.65 19.34 19.34 23.81
#> 37 117 108 192 90 45 171 92 37.1 171.1 110.1 136.2 170
#> 12.52 17.46 18.29 16.44 20.94 17.42 16.57 22.92 12.52 16.57 17.56 21.83 19.54
#> 194 175 77.1 168 107 8 66 113 167 101 18 107.1 169
#> 22.40 21.91 7.27 23.72 11.18 18.43 22.13 22.86 15.55 9.97 15.21 11.18 22.41
#> 52 123.1 197 140 61 14 92.1 85.1 130.2 183 194.1 26 155
#> 10.42 13.00 21.60 12.68 10.12 12.89 22.92 16.44 16.47 9.24 22.40 15.77 13.08
#> 18.1 100 184 181 36 66.1 108.1 139 171.2 111 105 24 180
#> 15.21 16.07 17.77 16.46 21.19 22.13 18.29 21.49 16.57 17.45 19.75 23.89 14.82
#> 86.2 130.3 117.1 133.1 153 194.2 134 78 111.1 23.1 129 110.2 57.1
#> 23.81 16.47 17.46 14.65 21.33 22.40 17.81 23.88 17.45 16.92 23.41 17.56 14.46
#> 90.1 78.1 128.1 60 194.3 30 113.1 175.1 155.1 15 19 12 118
#> 20.94 23.88 20.35 13.15 22.40 17.43 22.86 21.91 13.08 22.68 24.00 24.00 24.00
#> 138 104 33 137 144 65 1 3 196 191 176 47 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 104.1 163 172 7 147 173 152 62 118.1 172.1 72 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 120 148 151 11 146 122 12.1 186 98 48 178 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 137.1 33.1 31 31.1 148.1 82 165 121 17 122.1 147.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 118.3 182 109 31.2 44 122.2 173.2 80 12.2 75 144.1 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 109.1 35 20 2 47.1 27 172.3 112 80.1 141 178.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 172.4 165.1 138.1 172.5
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002773868 0.187969687 0.151831305
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.32628361 0.01728725 0.91043232
#> grade_iii, Cure model
#> 1.29170448
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 177 12.53 1 75 0 0
#> 187 9.92 1 39 1 0
#> 195 11.76 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 49 12.19 1 48 1 0
#> 5 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 68 20.62 1 44 0 0
#> 59 10.16 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 188 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 78 23.88 1 43 0 0
#> 183 9.24 1 67 1 0
#> 166 19.98 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 129 23.41 1 53 1 0
#> 175 21.91 1 43 0 0
#> 14 12.89 1 21 0 0
#> 41.1 18.02 1 40 1 0
#> 159 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 197.1 21.60 1 69 1 0
#> 129.1 23.41 1 53 1 0
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 136 21.83 1 43 0 1
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 127.1 3.53 1 62 0 1
#> 16 8.71 1 71 0 1
#> 149 8.37 1 33 1 0
#> 129.2 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 5.1 16.43 1 51 0 1
#> 50 10.02 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 69 23.23 1 25 0 1
#> 114.1 13.68 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 41.2 18.02 1 40 1 0
#> 37 12.52 1 57 1 0
#> 57 14.46 1 45 0 1
#> 166.1 19.98 1 48 0 0
#> 149.1 8.37 1 33 1 0
#> 150.1 20.33 1 48 0 0
#> 23 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 171 16.57 1 41 0 1
#> 4 17.64 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 195.1 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 86 23.81 1 58 0 1
#> 23.1 16.92 1 61 0 0
#> 16.1 8.71 1 71 0 1
#> 60 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 128 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 26.1 15.77 1 49 0 1
#> 37.1 12.52 1 57 1 0
#> 23.2 16.92 1 61 0 0
#> 5.2 16.43 1 51 0 1
#> 106 16.67 1 49 1 0
#> 96 14.54 1 33 0 1
#> 117 17.46 1 26 0 1
#> 52 10.42 1 52 0 1
#> 180 14.82 1 37 0 0
#> 70 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 96.1 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 164 23.60 1 76 0 1
#> 150.2 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 150.3 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 166.2 19.98 1 48 0 0
#> 86.1 23.81 1 58 0 1
#> 128.1 20.35 1 35 0 1
#> 57.1 14.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 69.1 23.23 1 25 0 1
#> 29.1 15.45 1 68 1 0
#> 36.1 21.19 1 48 0 1
#> 150.4 20.33 1 48 0 0
#> 49.1 12.19 1 48 1 0
#> 129.3 23.41 1 53 1 0
#> 41.3 18.02 1 40 1 0
#> 175.1 21.91 1 43 0 0
#> 63 22.77 1 31 1 0
#> 55 19.34 1 69 0 1
#> 101 9.97 1 10 0 1
#> 68.2 20.62 1 44 0 0
#> 136.1 21.83 1 43 0 1
#> 32.1 20.90 1 37 1 0
#> 91 5.33 1 61 0 1
#> 77 7.27 1 67 0 1
#> 51 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 177.2 12.53 1 75 0 0
#> 86.2 23.81 1 58 0 1
#> 82 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 35 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 67 24.00 0 25 0 0
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 112 24.00 0 61 0 0
#> 74 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 109 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 62 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 119.1 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 147 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 112.2 24.00 0 61 0 0
#> 28.1 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 126 24.00 0 48 0 0
#> 119.2 24.00 0 17 0 0
#> 163 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 95.1 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 172.1 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 196.1 24.00 0 19 0 0
#> 12 24.00 0 63 0 0
#> 74.1 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 156 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 17 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 132.1 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 112.3 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 196.2 24.00 0 19 0 0
#> 47.1 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 162.1 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 19.1 24.00 0 57 0 1
#> 163.1 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 151.2 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 53.1 24.00 0 32 0 1
#> 33.1 24.00 0 53 0 0
#> 54.1 24.00 0 53 1 0
#> 34.1 24.00 0 36 0 0
#> 98.1 24.00 0 34 1 0
#> 143.1 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 84.1 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.33 NA NA NA
#> 2 age, Cure model 0.0173 NA NA NA
#> 3 grade_ii, Cure model 0.910 NA NA NA
#> 4 grade_iii, Cure model 1.29 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00277 NA NA NA
#> 2 grade_ii, Survival model 0.188 NA NA NA
#> 3 grade_iii, Survival model 0.152 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.32628 0.01729 0.91043 1.29170
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.32628361 0.01728725 0.91043232 1.29170448
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002773868 0.187969687 0.151831305
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.27866570 0.82351015 0.91702198 0.82351015 0.87057677 0.64254187
#> [7] 0.63390276 0.49225233 0.35067033 0.48286961 0.34053797 0.66777026
#> [13] 0.52008066 0.02350195 0.92470679 0.44541783 0.22272572 0.11774287
#> [19] 0.23437333 0.80750987 0.52008066 0.88608624 0.61656147 0.27866570
#> [25] 0.11774287 0.98514342 0.39932627 0.25681604 0.50156514 0.32036439
#> [31] 0.98514342 0.93236275 0.94750845 0.11774287 0.90159498 0.55514452
#> [37] 0.64254187 0.68471658 0.16317943 0.70978406 0.52008066 0.84707263
#> [43] 0.77536608 0.44541783 0.94750845 0.39932627 0.57298432 0.81552655
#> [49] 0.60782879 0.35067033 0.62525127 0.71813715 0.05709096 0.57298432
#> [55] 0.93236275 0.79948842 0.79143944 0.37987992 0.68471658 0.84707263
#> [61] 0.57298432 0.64254187 0.59905780 0.75918583 0.56408212 0.89385220
#> [67] 0.75100384 0.96257647 0.70140240 0.75918583 0.72645063 0.67625303
#> [73] 0.10133889 0.39932627 0.29975370 0.86273404 0.74281220 0.39932627
#> [79] 0.18687230 0.44541783 0.05709096 0.37987992 0.77536608 0.21098100
#> [85] 0.16317943 0.72645063 0.29975370 0.39932627 0.87057677 0.11774287
#> [91] 0.52008066 0.23437333 0.19904153 0.47342226 0.90931492 0.35067033
#> [97] 0.25681604 0.32036439 0.97764350 0.97012174 0.51086192 0.82351015
#> [103] 0.05709096 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 197 177 187 177.1 49 5 85 97 68 76 190 188 41
#> 21.60 12.53 9.92 12.53 12.19 16.43 16.44 19.14 20.62 19.22 20.81 16.16 18.02
#> 78 183 166 66 129 175 14 41.1 159 130 197.1 129.1 127
#> 23.88 9.24 19.98 22.13 23.41 21.91 12.89 18.02 10.55 16.47 21.60 23.41 3.53
#> 150 136 8 32 127.1 16 149 129.2 93 40 5.1 26 69
#> 20.33 21.83 18.43 20.90 3.53 8.71 8.37 23.41 10.33 18.00 16.43 15.77 23.23
#> 39 41.2 37 57 166.1 149.1 150.1 23 140 171 68.1 181 167
#> 15.59 18.02 12.52 14.46 19.98 8.37 20.33 16.92 12.68 16.57 20.62 16.46 15.55
#> 86 23.1 16.1 60 13 128 26.1 37.1 23.2 5.2 106 96 117
#> 23.81 16.92 8.71 13.15 14.34 20.35 15.77 12.52 16.92 16.43 16.67 14.54 17.46
#> 52 180 70 6 96.1 29 100 164 150.2 36 42 18 150.3
#> 10.42 14.82 7.38 15.64 14.54 15.45 16.07 23.60 20.33 21.19 12.43 15.21 20.33
#> 113 166.2 86.1 128.1 57.1 194 69.1 29.1 36.1 150.4 49.1 129.3 41.3
#> 22.86 19.98 23.81 20.35 14.46 22.40 23.23 15.45 21.19 20.33 12.19 23.41 18.02
#> 175.1 63 55 101 68.2 136.1 32.1 91 77 51 177.2 86.2 82
#> 21.91 22.77 19.34 9.97 20.62 21.83 20.90 5.33 7.27 18.23 12.53 23.81 24.00
#> 200 53 35 44 67 83 119 112 74 75 109 112.1 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 34 62 162 132 119.1 172 196 147 62.1 84 3 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 1 182 22 152 47 28 174 193 112.2 28.1 151 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 2 126 119.2 163 94 95.1 80 172.1 120 196.1 12 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 165 156 54 17 12.1 132.1 141 156.1 33 143 112.3 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 196.2 47.1 7 162.1 48 148 19.1 163.1 151.1 87 151.2 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 33.1 54.1 34.1 98.1 143.1 35.1 137 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001000104 0.443417316 0.269977774
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.71549195 0.01016543 0.33314660
#> grade_iii, Cure model
#> 0.86032539
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 43 12.10 1 61 0 1
#> 41 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 184 17.77 1 38 0 0
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 88 18.37 1 47 0 0
#> 190 20.81 1 42 1 0
#> 5 16.43 1 51 0 1
#> 136 21.83 1 43 0 1
#> 14 12.89 1 21 0 0
#> 91.1 5.33 1 61 0 1
#> 155 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 13 14.34 1 54 0 1
#> 39 15.59 1 37 0 1
#> 108 18.29 1 39 0 1
#> 76 19.22 1 54 0 1
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 145.1 10.07 1 65 1 0
#> 192 16.44 1 31 1 0
#> 18 15.21 1 49 1 0
#> 117 17.46 1 26 0 1
#> 101 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 192.1 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 130.1 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 155.1 13.08 1 26 0 0
#> 40 18.00 1 28 1 0
#> 105 19.75 1 60 0 0
#> 107 11.18 1 54 1 0
#> 43.1 12.10 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 150 20.33 1 48 0 0
#> 37 12.52 1 57 1 0
#> 24 23.89 1 38 0 0
#> 128 20.35 1 35 0 1
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 4.1 17.64 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 52 10.42 1 52 0 1
#> 13.1 14.34 1 54 0 1
#> 177 12.53 1 75 0 0
#> 169 22.41 1 46 0 0
#> 169.1 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 136.1 21.83 1 43 0 1
#> 51 18.23 1 83 0 1
#> 70 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 79 16.23 1 54 1 0
#> 76.1 19.22 1 54 0 1
#> 29 15.45 1 68 1 0
#> 36 21.19 1 48 0 1
#> 124 9.73 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 41.1 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 40.1 18.00 1 28 1 0
#> 29.1 15.45 1 68 1 0
#> 26 15.77 1 49 0 1
#> 14.1 12.89 1 21 0 0
#> 50 10.02 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 56 12.21 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 60 13.15 1 38 1 0
#> 199.1 19.81 1 NA 0 1
#> 180.1 14.82 1 37 0 0
#> 153 21.33 1 55 1 0
#> 59.1 10.16 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 195 11.76 1 NA 1 0
#> 145.2 10.07 1 65 1 0
#> 25 6.32 1 34 1 0
#> 66.1 22.13 1 53 0 0
#> 167 15.55 1 56 1 0
#> 153.1 21.33 1 55 1 0
#> 157 15.10 1 47 0 0
#> 96 14.54 1 33 0 1
#> 153.2 21.33 1 55 1 0
#> 36.1 21.19 1 48 0 1
#> 37.1 12.52 1 57 1 0
#> 99 21.19 1 38 0 1
#> 136.2 21.83 1 43 0 1
#> 90 20.94 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 188 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 194 22.40 1 38 0 1
#> 184.1 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 79.2 16.23 1 54 1 0
#> 181.1 16.46 1 45 0 1
#> 184.2 17.77 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 72 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 33 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 31.1 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 160.1 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 12 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 193 24.00 0 45 0 1
#> 132 24.00 0 55 0 0
#> 72.1 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 7.1 24.00 0 37 1 0
#> 131 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 152 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 103.1 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 95.1 24.00 0 68 0 1
#> 103.2 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 126 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 147.1 24.00 0 76 1 0
#> 19.1 24.00 0 57 0 1
#> 33.1 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 182.1 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 141.2 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 152.1 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 12.2 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 132.1 24.00 0 55 0 0
#> 65.1 24.00 0 57 1 0
#> 65.2 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 64 24.00 0 43 0 0
#> 11.1 24.00 0 42 0 1
#> 141.3 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 38.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 21.1 24.00 0 47 0 0
#> 7.2 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 83.1 24.00 0 6 0 0
#> 163.2 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 64.1 24.00 0 43 0 0
#> 73.1 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 120 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.715 NA NA NA
#> 2 age, Cure model 0.0102 NA NA NA
#> 3 grade_ii, Cure model 0.333 NA NA NA
#> 4 grade_iii, Cure model 0.860 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00100 NA NA NA
#> 2 grade_ii, Survival model 0.443 NA NA NA
#> 3 grade_iii, Survival model 0.270 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71549 0.01017 0.33315 0.86033
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71549195 0.01016543 0.33314660 0.86032539
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001000104 0.443417316 0.269977774
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86298378 0.40869678 0.08240598 0.45688440 0.97630028 0.52278483
#> [7] 0.53228286 0.92840187 0.37811645 0.29545298 0.60577005 0.17378808
#> [13] 0.77914411 0.97630028 0.76223502 0.28474462 0.73674431 0.65897931
#> [19] 0.38837424 0.34768957 0.06555348 0.14788968 0.92840187 0.57876024
#> [25] 0.69378294 0.48500729 0.95233041 0.54173749 0.33730043 0.57876024
#> [31] 0.79606085 0.54173749 0.57876024 0.36787144 0.76223502 0.42823939
#> [37] 0.32683959 0.87945022 0.86298378 0.02837239 0.31639825 0.82136595
#> [43] 0.01004105 0.30597306 0.84644402 0.84644402 0.50398136 0.91218715
#> [49] 0.89590194 0.73674431 0.80451702 0.10827340 0.10827340 0.49451706
#> [55] 0.17378808 0.39856213 0.96035422 0.04775495 0.61487691 0.34768957
#> [61] 0.67656626 0.24207734 0.71100867 0.40869678 0.56032597 0.42823939
#> [67] 0.67656626 0.65012736 0.77914411 0.61487691 0.83805343 0.91218715
#> [73] 0.89590194 0.44733347 0.75373793 0.71100867 0.20924380 0.50398136
#> [79] 0.92840187 0.96834386 0.14788968 0.66780018 0.20924380 0.70239338
#> [85] 0.72814988 0.20924380 0.24207734 0.82136595 0.24207734 0.17378808
#> [91] 0.27383053 0.08240598 0.64124551 0.99208873 0.13445136 0.45688440
#> [97] 0.88768546 0.61487691 0.56032597 0.45688440 0.80451702 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 43 41 129 184 91 23 171 145 88 190 5 136 14
#> 12.10 18.02 23.41 17.77 5.33 16.92 16.57 10.07 18.37 20.81 16.43 21.83 12.89
#> 91.1 155 32 13 39 108 76 164 66 145.1 192 18 117
#> 5.33 13.08 20.90 14.34 15.59 18.29 19.22 23.60 22.13 10.07 16.44 15.21 17.46
#> 101 130 55 192.1 154 130.1 85 179 155.1 40 105 107 43.1
#> 9.97 16.47 19.34 16.44 12.63 16.47 16.44 18.63 13.08 18.00 19.75 11.18 12.10
#> 78 150 37 24 128 49 49.1 30 93 52 13.1 177 169
#> 23.88 20.33 12.52 23.89 20.35 12.19 12.19 17.43 10.33 10.42 14.34 12.53 22.41
#> 169.1 111 136.1 51 70 86 79 76.1 29 36 180 41.1 181
#> 22.41 17.45 21.83 18.23 7.38 23.81 16.23 19.22 15.45 21.19 14.82 18.02 16.46
#> 40.1 29.1 26 14.1 79.1 56 93.1 52.1 134 60 180.1 153 30.1
#> 18.00 15.45 15.77 12.89 16.23 12.21 10.33 10.42 17.81 13.15 14.82 21.33 17.43
#> 145.2 25 66.1 167 153.1 157 96 153.2 36.1 37.1 99 136.2 90
#> 10.07 6.32 22.13 15.55 21.33 15.10 14.54 21.33 21.19 12.52 21.19 21.83 20.94
#> 129.1 188 127 194 184.1 159 79.2 181.1 184.2 177.1 72 200 33
#> 23.41 16.16 3.53 22.40 17.77 10.55 16.23 16.46 17.77 12.53 24.00 24.00 24.00
#> 62 31 94 75 103 31.1 7 80 95 19 53 160 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 144 141 163 182 12 46 173 193 132 72.1 148 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 141.1 28 102 152 2 103.1 44 95.1 103.2 82 126 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 12.1 147.1 19.1 33.1 162 53.1 122 21 11 182.1 138 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 38 75.1 84 83 152.1 65 9 67 12.2 191 132.1 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 67.1 64 11.1 141.3 75.2 38.1 151 121 21.1 7.2 135 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.2 22 64.1 174 120
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008032438 0.318240597 0.165574989
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.15229972 0.01122129 -0.86564449
#> grade_iii, Cure model
#> 0.47886481
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 57 14.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 157 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 81 14.06 1 34 0 0
#> 113 22.86 1 34 0 0
#> 170 19.54 1 43 0 1
#> 180 14.82 1 37 0 0
#> 81.1 14.06 1 34 0 0
#> 81.2 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 57.1 14.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 123 13.00 1 44 1 0
#> 13 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 184 17.77 1 38 0 0
#> 14 12.89 1 21 0 0
#> 81.3 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 6.1 15.64 1 39 0 0
#> 127 3.53 1 62 0 1
#> 10 10.53 1 34 0 0
#> 190 20.81 1 42 1 0
#> 42 12.43 1 49 0 1
#> 85 16.44 1 36 0 0
#> 89 11.44 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 175 21.91 1 43 0 0
#> 159 10.55 1 50 0 1
#> 76 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 107 11.18 1 54 1 0
#> 175.1 21.91 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 41 18.02 1 40 1 0
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 37.1 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 177 12.53 1 75 0 0
#> 23 16.92 1 61 0 0
#> 180.1 14.82 1 37 0 0
#> 30.1 17.43 1 78 0 0
#> 145 10.07 1 65 1 0
#> 169.1 22.41 1 46 0 0
#> 81.4 14.06 1 34 0 0
#> 170.1 19.54 1 43 0 1
#> 97.1 19.14 1 65 0 1
#> 164 23.60 1 76 0 1
#> 107.1 11.18 1 54 1 0
#> 90.1 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 37.2 12.52 1 57 1 0
#> 10.1 10.53 1 34 0 0
#> 10.2 10.53 1 34 0 0
#> 45 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 188 16.16 1 46 0 1
#> 23.1 16.92 1 61 0 0
#> 117 17.46 1 26 0 1
#> 66 22.13 1 53 0 0
#> 127.1 3.53 1 62 0 1
#> 167 15.55 1 56 1 0
#> 181 16.46 1 45 0 1
#> 14.1 12.89 1 21 0 0
#> 5 16.43 1 51 0 1
#> 66.1 22.13 1 53 0 0
#> 129 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 16 8.71 1 71 0 1
#> 168 23.72 1 70 0 0
#> 159.1 10.55 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 199 19.81 1 NA 0 1
#> 175.2 21.91 1 43 0 0
#> 91 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 184.1 17.77 1 38 0 0
#> 180.2 14.82 1 37 0 0
#> 23.2 16.92 1 61 0 0
#> 170.2 19.54 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 180.3 14.82 1 37 0 0
#> 85.1 16.44 1 36 0 0
#> 85.2 16.44 1 36 0 0
#> 166 19.98 1 48 0 0
#> 58 19.34 1 39 0 0
#> 49 12.19 1 48 1 0
#> 127.2 3.53 1 62 0 1
#> 63 22.77 1 31 1 0
#> 124.1 9.73 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 194 22.40 1 38 0 1
#> 105.1 19.75 1 60 0 0
#> 153 21.33 1 55 1 0
#> 40.1 18.00 1 28 1 0
#> 155 13.08 1 26 0 0
#> 59.1 10.16 1 NA 1 0
#> 57.2 14.46 1 45 0 1
#> 194.1 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 55 19.34 1 69 0 1
#> 45.1 17.42 1 54 0 1
#> 88 18.37 1 47 0 0
#> 60 13.15 1 38 1 0
#> 47 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 75 24.00 0 21 1 0
#> 118 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 118.1 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 104 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 144 24.00 0 28 0 1
#> 172 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 120 24.00 0 68 0 1
#> 144.1 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 1 24.00 0 23 1 0
#> 116 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 48 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 2 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 98 24.00 0 34 1 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 11.1 24.00 0 42 0 1
#> 137 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 200.1 24.00 0 64 0 0
#> 131 24.00 0 66 0 0
#> 178.2 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 27 24.00 0 63 1 0
#> 131.1 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 44.1 24.00 0 56 0 0
#> 151.1 24.00 0 42 0 0
#> 87.1 24.00 0 27 0 0
#> 112 24.00 0 61 0 0
#> 1.1 24.00 0 23 1 0
#> 19.1 24.00 0 57 0 1
#> 65.1 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 98.1 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 142.1 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 191 24.00 0 60 0 1
#> 27.1 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 156.1 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 115.1 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 141.2 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 22.1 24.00 0 52 1 0
#> 165.1 24.00 0 47 0 0
#> 47.1 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.152 NA NA NA
#> 2 age, Cure model 0.0112 NA NA NA
#> 3 grade_ii, Cure model -0.866 NA NA NA
#> 4 grade_iii, Cure model 0.479 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00803 NA NA NA
#> 2 grade_ii, Survival model 0.318 NA NA NA
#> 3 grade_iii, Survival model 0.166 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.15230 0.01122 -0.86564 0.47886
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 246.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.15229972 0.01122129 -0.86564449 0.47886481
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008032438 0.318240597 0.165574989
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.283253237 0.585907262 0.479403158 0.532300932 0.339119686 0.629786331
#> [7] 0.028791488 0.177375417 0.543106535 0.629786331 0.629786331 0.136701728
#> [13] 0.585907262 0.753157713 0.113819062 0.707491987 0.618632575 0.500364044
#> [19] 0.310943919 0.718892297 0.629786331 0.928043907 0.500364044 0.963990540
#> [25] 0.857224278 0.128911586 0.787436333 0.417652506 0.237137678 0.085195985
#> [31] 0.833898679 0.219491579 0.023000643 0.810709495 0.085195985 0.479403158
#> [37] 0.046372239 0.273862592 0.017480975 0.753157713 0.892313659 0.741623198
#> [43] 0.377783381 0.543106535 0.339119686 0.916108683 0.046372239 0.629786331
#> [49] 0.177375417 0.237137678 0.006863682 0.810709495 0.113819062 0.904202070
#> [55] 0.753157713 0.857224278 0.857224278 0.358328776 0.160825864 0.458439329
#> [61] 0.377783381 0.329629187 0.071569024 0.963990540 0.521563871 0.407463548
#> [67] 0.718892297 0.448025138 0.071569024 0.012034940 0.255187019 0.939978368
#> [73] 0.001187193 0.833898679 0.001187193 0.085195985 0.951963478 0.301606590
#> [79] 0.310943919 0.543106535 0.377783381 0.177375417 0.028791488 0.543106535
#> [85] 0.417652506 0.417652506 0.152657361 0.202173548 0.799067396 0.963990540
#> [91] 0.040237322 0.219491579 0.468897353 0.058790165 0.160825864 0.106225231
#> [97] 0.283253237 0.696098029 0.585907262 0.058790165 0.144626408 0.202173548
#> [103] 0.358328776 0.264472961 0.684739117 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 40 57 125 157 30 81 113 170 180 81.1 81.2 68 57.1
#> 18.00 14.46 15.65 15.10 17.43 14.06 22.86 19.54 14.82 14.06 14.06 20.62 14.46
#> 37 90 123 13 6 184 14 81.3 187 6.1 127 10 190
#> 12.52 20.94 13.00 14.34 15.64 17.77 12.89 14.06 9.92 15.64 3.53 10.53 20.81
#> 42 85 97 175 159 76 92 107 175.1 125.1 169 41 69
#> 12.43 16.44 19.14 21.91 10.55 19.22 22.92 11.18 21.91 15.65 22.41 18.02 23.23
#> 37.1 52 177 23 180.1 30.1 145 169.1 81.4 170.1 97.1 164 107.1
#> 12.52 10.42 12.53 16.92 14.82 17.43 10.07 22.41 14.06 19.54 19.14 23.60 11.18
#> 90.1 61 37.2 10.1 10.2 45 105 188 23.1 117 66 127.1 167
#> 20.94 10.12 12.52 10.53 10.53 17.42 19.75 16.16 16.92 17.46 22.13 3.53 15.55
#> 181 14.1 5 66.1 129 179 16 168 159.1 168.1 175.2 91 134
#> 16.46 12.89 16.43 22.13 23.41 18.63 8.71 23.72 10.55 23.72 21.91 5.33 17.81
#> 184.1 180.2 23.2 170.2 113.1 180.3 85.1 85.2 166 58 49 127.2 63
#> 17.77 14.82 16.92 19.54 22.86 14.82 16.44 16.44 19.98 19.34 12.19 3.53 22.77
#> 76.1 26 194 105.1 153 40.1 155 57.2 194.1 158 55 45.1 88
#> 19.22 15.77 22.40 19.75 21.33 18.00 13.08 14.46 22.40 20.14 19.34 17.42 18.37
#> 60 47 80 19 65 75 118 142 151 141 44 118.1 22
#> 13.15 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 11 104 193 34 144 172 46 143 9 141.1 103 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 120 144.1 143.1 162 178 185 82 1 116 178.1 87 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 2 21 200 98 165 12 11.1 137 54 200.1 131 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 67 27 131.1 138 48.1 161 44.1 151.1 87.1 112 1.1 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 95 156 98.1 174 142.1 12.1 135 191 27.1 156.1 3 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 146 141.2 22.1 165.1 47.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005293795 0.756553375 0.642741060
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.84854736 0.01171423 0.27649529
#> grade_iii, Cure model
#> 1.56211066
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 136 21.83 1 43 0 1
#> 133 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 85 16.44 1 36 0 0
#> 169 22.41 1 46 0 0
#> 76 19.22 1 54 0 1
#> 177 12.53 1 75 0 0
#> 70 7.38 1 30 1 0
#> 37 12.52 1 57 1 0
#> 39 15.59 1 37 0 1
#> 42 12.43 1 49 0 1
#> 139 21.49 1 63 1 0
#> 93 10.33 1 52 0 1
#> 57 14.46 1 45 0 1
#> 159 10.55 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 70.1 7.38 1 30 1 0
#> 42.1 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 37.1 12.52 1 57 1 0
#> 24 23.89 1 38 0 0
#> 45 17.42 1 54 0 1
#> 42.2 12.43 1 49 0 1
#> 168 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 25 6.32 1 34 1 0
#> 29 15.45 1 68 1 0
#> 40 18.00 1 28 1 0
#> 133.1 14.65 1 57 0 0
#> 140 12.68 1 59 1 0
#> 180.1 14.82 1 37 0 0
#> 37.2 12.52 1 57 1 0
#> 183.1 9.24 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 128 20.35 1 35 0 1
#> 188.1 16.16 1 46 0 1
#> 29.1 15.45 1 68 1 0
#> 76.2 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 113 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 29.2 15.45 1 68 1 0
#> 49.1 12.19 1 48 1 0
#> 155 13.08 1 26 0 0
#> 177.1 12.53 1 75 0 0
#> 91 5.33 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 194 22.40 1 38 0 1
#> 114.1 13.68 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 128.1 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 58.1 19.34 1 39 0 0
#> 154 12.63 1 20 1 0
#> 168.1 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 91.1 5.33 1 61 0 1
#> 154.1 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 125 15.65 1 67 1 0
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 140.1 12.68 1 59 1 0
#> 49.2 12.19 1 48 1 0
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 89.1 11.44 1 NA 0 0
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 76.3 19.22 1 54 0 1
#> 127.1 3.53 1 62 0 1
#> 30 17.43 1 78 0 0
#> 128.2 20.35 1 35 0 1
#> 199 19.81 1 NA 0 1
#> 24.1 23.89 1 38 0 0
#> 114.2 13.68 1 NA 0 0
#> 85.1 16.44 1 36 0 0
#> 42.3 12.43 1 49 0 1
#> 197 21.60 1 69 1 0
#> 50 10.02 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 59.1 10.16 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 41.1 18.02 1 40 1 0
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 192 16.44 1 31 1 0
#> 16 8.71 1 71 0 1
#> 68 20.62 1 44 0 0
#> 194.2 22.40 1 38 0 1
#> 81.1 14.06 1 34 0 0
#> 50.1 10.02 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 5 16.43 1 51 0 1
#> 164 23.60 1 76 0 1
#> 127.2 3.53 1 62 0 1
#> 101 9.97 1 10 0 1
#> 190.1 20.81 1 42 1 0
#> 52 10.42 1 52 0 1
#> 8 18.43 1 32 0 0
#> 137 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 148 24.00 0 61 1 0
#> 104 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 27 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 1.1 24.00 0 23 1 0
#> 98 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 82 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 132.1 24.00 0 55 0 0
#> 109 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 12.1 24.00 0 63 0 0
#> 82.1 24.00 0 34 0 0
#> 172.1 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 67.1 24.00 0 25 0 0
#> 121 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 182 24.00 0 35 0 0
#> 98.1 24.00 0 34 1 0
#> 67.2 24.00 0 25 0 0
#> 135 24.00 0 58 1 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 28 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 83.1 24.00 0 6 0 0
#> 116.1 24.00 0 58 0 1
#> 144 24.00 0 28 0 1
#> 135.1 24.00 0 58 1 0
#> 19.1 24.00 0 57 0 1
#> 186.1 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 178 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 138 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 7 24.00 0 37 1 0
#> 143 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 163.1 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 54.1 24.00 0 53 1 0
#> 151.1 24.00 0 42 0 0
#> 160 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 162 24.00 0 51 0 0
#> 142.2 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 161 24.00 0 45 0 0
#> 148.1 24.00 0 61 1 0
#> 21 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 83.2 24.00 0 6 0 0
#> 67.3 24.00 0 25 0 0
#> 103.1 24.00 0 56 1 0
#> 98.2 24.00 0 34 1 0
#> 132.2 24.00 0 55 0 0
#> 34 24.00 0 36 0 0
#> 163.2 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 33.1 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 28.1 24.00 0 67 1 0
#> 186.2 24.00 0 45 1 0
#> 104.1 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.849 NA NA NA
#> 2 age, Cure model 0.0117 NA NA NA
#> 3 grade_ii, Cure model 0.276 NA NA NA
#> 4 grade_iii, Cure model 1.56 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00529 NA NA NA
#> 2 grade_ii, Survival model 0.757 NA NA NA
#> 3 grade_iii, Survival model 0.643 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84855 0.01171 0.27650 1.56211
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 241.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84854736 0.01171423 0.27649529 1.56211066
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005293795 0.756553375 0.642741060
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.40079091 0.79609792 0.71882254 0.68271287 0.32506410 0.56169310
#> [7] 0.85529252 0.96352018 0.86664226 0.74617979 0.88300813 0.42790184
#> [13] 0.92947727 0.80823133 0.91932920 0.90400397 0.96352018 0.88300813
#> [19] 0.78389903 0.86664226 0.06086729 0.66768677 0.88300813 0.13789244
#> [25] 0.94920738 0.97286094 0.75284815 0.64450242 0.79609792 0.83222960
#> [31] 0.78389903 0.86664226 0.94920738 0.56169310 0.45207604 0.48437686
#> [37] 0.71882254 0.75284815 0.56169310 0.30670611 0.52349600 0.24809568
#> [43] 0.67521575 0.75284815 0.90400397 0.82622841 0.85529252 0.97750790
#> [49] 0.34314095 0.54287636 0.92947727 0.48437686 0.44025293 0.54287636
#> [55] 0.84386890 0.13789244 0.51361444 0.34314095 0.97750790 0.84386890
#> [61] 0.77165892 0.73943224 0.53330833 0.81425682 0.77165892 0.22655028
#> [67] 0.83222960 0.90400397 0.93939421 0.98663886 0.60369198 0.62868439
#> [73] 0.56169310 0.98663886 0.66002554 0.48437686 0.06086729 0.68271287
#> [79] 0.88300813 0.41480438 0.24809568 0.73255682 0.28802507 0.65231857
#> [85] 0.38606292 0.62868439 0.71172805 0.62038159 0.68271287 0.95876927
#> [91] 0.47357010 0.34314095 0.81425682 0.59530778 0.70450131 0.20049963
#> [97] 0.98663886 0.94431361 0.45207604 0.92442418 0.61204728 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 136 133 188 85 169 76 177 70 37 39 42 139 93
#> 21.83 14.65 16.16 16.44 22.41 19.22 12.53 7.38 12.52 15.59 12.43 21.49 10.33
#> 57 159 49 70.1 42.1 180 37.1 24 45 42.2 168 183 25
#> 14.46 10.55 12.19 7.38 12.43 14.82 12.52 23.89 17.42 12.43 23.72 9.24 6.32
#> 29 40 133.1 140 180.1 37.2 183.1 76.1 190 128 188.1 29.1 76.2
#> 15.45 18.00 14.65 12.68 14.82 12.52 9.24 19.22 20.81 20.35 16.16 15.45 19.22
#> 15 105 113 23 29.2 49.1 155 177.1 91 194 58 93.1 128.1
#> 22.68 19.75 22.86 16.92 15.45 12.19 13.08 12.53 5.33 22.40 19.34 10.33 20.35
#> 32 58.1 154 168.1 150 194.1 91.1 154.1 18 125 170 81 18.1
#> 20.90 19.34 12.63 23.72 20.33 22.40 5.33 12.63 15.21 15.65 19.54 14.06 15.21
#> 129 140.1 49.2 145 127 179 41 76.3 127.1 30 128.2 24.1 85.1
#> 23.41 12.68 12.19 10.07 3.53 18.63 18.02 19.22 3.53 17.43 20.35 23.89 16.44
#> 42.3 197 113.1 100 63 117 175 41.1 79 88 192 16 68
#> 12.43 21.60 22.86 16.07 22.77 17.46 21.91 18.02 16.23 18.37 16.44 8.71 20.62
#> 194.2 81.1 97 5 164 127.2 101 190.1 52 8 137 193 1
#> 22.40 14.06 19.14 16.43 23.60 3.53 9.97 20.81 10.42 18.43 24.00 24.00 24.00
#> 148 104 185 2 12 27 172 22 71 122 132 1.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 82 67 132.1 109 19 9 174 12.1 82.1 172.1 146 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 121 83 182 98.1 67.2 135 35 151 87 28 163 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 116.1 144 135.1 19.1 186.1 64 178 102 138 33 142 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 7 143 74 163.1 65 54.1 151.1 160 84 162 142.2 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 161 148.1 21 121.1 72 83.2 67.3 103.1 98.2 132.2 34 163.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 33.1 28.1 186.2 104.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005585743 0.975905746 0.070226123
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.539369110 0.004387182 0.062553507
#> grade_iii, Cure model
#> 1.484562479
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 61 10.12 1 36 0 1
#> 52 10.42 1 52 0 1
#> 60 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 170 19.54 1 43 0 1
#> 145.1 10.07 1 65 1 0
#> 177 12.53 1 75 0 0
#> 170.1 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 13.1 14.34 1 54 0 1
#> 68 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 69 23.23 1 25 0 1
#> 127 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 168 23.72 1 70 0 0
#> 45.1 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 194 22.40 1 38 0 1
#> 128 20.35 1 35 0 1
#> 170.2 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 181 16.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 110 17.56 1 65 0 1
#> 86.1 23.81 1 58 0 1
#> 77 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 106 16.67 1 49 1 0
#> 169 22.41 1 46 0 0
#> 188 16.16 1 46 0 1
#> 25 6.32 1 34 1 0
#> 90.1 20.94 1 50 0 1
#> 70 7.38 1 30 1 0
#> 99 21.19 1 38 0 1
#> 58 19.34 1 39 0 0
#> 89 11.44 1 NA 0 0
#> 43 12.10 1 61 0 1
#> 70.1 7.38 1 30 1 0
#> 51.1 18.23 1 83 0 1
#> 10.1 10.53 1 34 0 0
#> 86.2 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 175 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 26 15.77 1 49 0 1
#> 195 11.76 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 81 14.06 1 34 0 0
#> 194.1 22.40 1 38 0 1
#> 184 17.77 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 195.1 11.76 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 194.2 22.40 1 38 0 1
#> 6 15.64 1 39 0 0
#> 10.2 10.53 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 175.2 21.91 1 43 0 0
#> 45.2 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 155 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 145.2 10.07 1 65 1 0
#> 195.2 11.76 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 168.1 23.72 1 70 0 0
#> 99.1 21.19 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 184.1 17.77 1 38 0 0
#> 108.1 18.29 1 39 0 1
#> 79.1 16.23 1 54 1 0
#> 168.2 23.72 1 70 0 0
#> 145.3 10.07 1 65 1 0
#> 63 22.77 1 31 1 0
#> 23.1 16.92 1 61 0 0
#> 177.1 12.53 1 75 0 0
#> 70.2 7.38 1 30 1 0
#> 130 16.47 1 53 0 1
#> 49.1 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 89.1 11.44 1 NA 0 0
#> 170.3 19.54 1 43 0 1
#> 90.2 20.94 1 50 0 1
#> 111 17.45 1 47 0 1
#> 61.2 10.12 1 36 0 1
#> 13.2 14.34 1 54 0 1
#> 139 21.49 1 63 1 0
#> 26.1 15.77 1 49 0 1
#> 128.1 20.35 1 35 0 1
#> 4.1 17.64 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 149 8.37 1 33 1 0
#> 170.4 19.54 1 43 0 1
#> 187 9.92 1 39 1 0
#> 195.3 11.76 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 134 17.81 1 47 1 0
#> 181.1 16.46 1 45 0 1
#> 160 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 82 24.00 0 34 0 0
#> 64 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 115 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 160.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 94 24.00 0 51 0 1
#> 104 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 2 24.00 0 9 0 0
#> 182 24.00 0 35 0 0
#> 120.1 24.00 0 68 0 1
#> 115.1 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 87 24.00 0 27 0 0
#> 200 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 27 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 119 24.00 0 17 0 0
#> 64.1 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 131.1 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 104.1 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 112 24.00 0 61 0 0
#> 156 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 156.1 24.00 0 50 1 0
#> 72.2 24.00 0 40 0 1
#> 200.1 24.00 0 64 0 0
#> 104.2 24.00 0 50 1 0
#> 116.1 24.00 0 58 0 1
#> 20.1 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 83.1 24.00 0 6 0 0
#> 20.2 24.00 0 46 1 0
#> 142.1 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 64.2 24.00 0 43 0 0
#> 94.1 24.00 0 51 0 1
#> 112.1 24.00 0 61 0 0
#> 178.1 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 148.1 24.00 0 61 1 0
#> 82.1 24.00 0 34 0 0
#> 161.1 24.00 0 45 0 0
#> 72.3 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 104.3 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.539 NA NA NA
#> 2 age, Cure model 0.00439 NA NA NA
#> 3 grade_ii, Cure model 0.0626 NA NA NA
#> 4 grade_iii, Cure model 1.48 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00559 NA NA NA
#> 2 grade_ii, Survival model 0.976 NA NA NA
#> 3 grade_iii, Survival model 0.0702 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.539369 0.004387 0.062554 1.484562
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 234.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.539369110 0.004387182 0.062553507 1.484562479
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005585743 0.975905746 0.070226123
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.616026183 0.849569387 0.819623407 0.668444345 0.403940259 0.173415363
#> [7] 0.879456273 0.467808827 0.240954493 0.879456273 0.709876339 0.240954493
#> [13] 0.839531800 0.616026183 0.201393338 0.780176968 0.330447802 0.435512839
#> [19] 0.052196484 0.981929709 0.007225315 0.026217745 0.403940259 0.521612979
#> [25] 0.090747087 0.211292948 0.240954493 0.605531154 0.489287669 0.790083879
#> [31] 0.382722050 0.007225315 0.963754736 0.699738665 0.457129692 0.081263473
#> [37] 0.542322923 0.972892920 0.173415363 0.936665998 0.154810898 0.288927766
#> [43] 0.760286914 0.936665998 0.330447802 0.790083879 0.007225315 0.309739598
#> [49] 0.117367850 0.770293735 0.689395235 0.573745889 0.563168532 0.647302815
#> [55] 0.090747087 0.361990153 0.117367850 0.647302815 0.090747087 0.594847599
#> [61] 0.790083879 0.117367850 0.403940259 0.230840079 0.819623407 0.678908864
#> [67] 0.299304059 0.879456273 0.740466403 0.026217745 0.154810898 0.849569387
#> [73] 0.361990153 0.309739598 0.521612979 0.026217745 0.879456273 0.063058346
#> [79] 0.435512839 0.709876339 0.936665998 0.478523884 0.740466403 0.730204231
#> [85] 0.240954493 0.173415363 0.393306115 0.849569387 0.616026183 0.145367459
#> [91] 0.573745889 0.211292948 0.072025078 0.542322923 0.981929709 0.927204181
#> [97] 0.240954493 0.917624383 0.510733176 0.351587156 0.489287669 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 13 61 52 60 45 90 145 171 170 145.1 177 170.1 93
#> 14.34 10.12 10.42 13.15 17.42 20.94 10.07 16.57 19.54 10.07 12.53 19.54 10.33
#> 13.1 68 159 51 23 69 127 86 168 45.1 79 194 128
#> 14.34 20.62 10.55 18.23 16.92 23.23 3.53 23.81 23.72 17.42 16.23 22.40 20.35
#> 170.2 18 181 10 110 86.1 77 154 106 169 188 25 90.1
#> 19.54 15.21 16.46 10.53 17.56 23.81 7.27 12.63 16.67 22.41 16.16 6.32 20.94
#> 70 99 58 43 70.1 51.1 10.1 86.2 108 175 107 140 26
#> 7.38 21.19 19.34 12.10 7.38 18.23 10.53 23.81 18.29 21.91 11.18 12.68 15.77
#> 100 81 194.1 184 175.1 81.1 194.2 6 10.2 175.2 45.2 105 52.1
#> 16.07 14.06 22.40 17.77 21.91 14.06 22.40 15.64 10.53 21.91 17.42 19.75 10.42
#> 155 8 145.2 49 168.1 99.1 61.1 184.1 108.1 79.1 168.2 145.3 63
#> 13.08 18.43 10.07 12.19 23.72 21.19 10.12 17.77 18.29 16.23 23.72 10.07 22.77
#> 23.1 177.1 70.2 130 49.1 42 170.3 90.2 111 61.2 13.2 139 26.1
#> 16.92 12.53 7.38 16.47 12.19 12.43 19.54 20.94 17.45 10.12 14.34 21.49 15.77
#> 128.1 15 188.1 127.1 149 170.4 187 85 134 181.1 160 172 67
#> 20.35 22.68 16.16 3.53 8.37 19.54 9.92 16.44 17.81 16.46 24.00 24.00 24.00
#> 120 48 131 185 137 135 82 64 196 72 28 21 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 22 83 75 20 178 33 160.1 103 94 104 132 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 120.1 161 87 200 38 72.1 144 27 34 119 64.1 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 131.1 2.1 146 62 191 104.1 11 112 156 162 142 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.2 200.1 104.2 116.1 20.1 31 182.1 83.1 20.2 142.1 118 146.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 94.1 112.1 178.1 95 121 109 65 148.1 82.1 161.1 72.3 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 104.3 162.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00615388 0.62925663 0.15335425
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.1183117814 -0.0001554406 0.0926059387
#> grade_iii, Cure model
#> 0.7744831176
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 76 19.22 1 54 0 1
#> 107 11.18 1 54 1 0
#> 111 17.45 1 47 0 1
#> 69 23.23 1 25 0 1
#> 51 18.23 1 83 0 1
#> 110 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 56 12.21 1 60 0 0
#> 157 15.10 1 47 0 0
#> 128 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 166 19.98 1 48 0 0
#> 15 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 183 9.24 1 67 1 0
#> 13 14.34 1 54 0 1
#> 76.1 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 199 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 61 10.12 1 36 0 1
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 61.1 10.12 1 36 0 1
#> 58 19.34 1 39 0 0
#> 51.1 18.23 1 83 0 1
#> 100.1 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 76.2 19.22 1 54 0 1
#> 180 14.82 1 37 0 0
#> 49 12.19 1 48 1 0
#> 107.1 11.18 1 54 1 0
#> 55 19.34 1 69 0 1
#> 101 9.97 1 10 0 1
#> 195 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 25 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 4.1 17.64 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 15.1 22.68 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 14.1 12.89 1 21 0 0
#> 90.1 20.94 1 50 0 1
#> 155.1 13.08 1 26 0 0
#> 24.1 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 5 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 25.1 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 25.2 6.32 1 34 1 0
#> 55.1 19.34 1 69 0 1
#> 63 22.77 1 31 1 0
#> 26 15.77 1 49 0 1
#> 79 16.23 1 54 1 0
#> 32 20.90 1 37 1 0
#> 92.1 22.92 1 47 0 1
#> 134 17.81 1 47 1 0
#> 5.1 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 45.1 17.42 1 54 0 1
#> 164 23.60 1 76 0 1
#> 18.1 15.21 1 49 1 0
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 86.1 23.81 1 58 0 1
#> 88 18.37 1 47 0 0
#> 188 16.16 1 46 0 1
#> 40 18.00 1 28 1 0
#> 68.1 20.62 1 44 0 0
#> 58.1 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 4.2 17.64 1 NA 0 1
#> 183.1 9.24 1 67 1 0
#> 130 16.47 1 53 0 1
#> 154.1 12.63 1 20 1 0
#> 114 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 36 21.19 1 48 0 1
#> 183.2 9.24 1 67 1 0
#> 79.1 16.23 1 54 1 0
#> 14.2 12.89 1 21 0 0
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 5.2 16.43 1 51 0 1
#> 117.1 17.46 1 26 0 1
#> 184 17.77 1 38 0 0
#> 25.3 6.32 1 34 1 0
#> 129 23.41 1 53 1 0
#> 170.1 19.54 1 43 0 1
#> 37 12.52 1 57 1 0
#> 169.1 22.41 1 46 0 0
#> 127.1 3.53 1 62 0 1
#> 68.2 20.62 1 44 0 0
#> 199.2 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 83 24.00 0 6 0 0
#> 22 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 95 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 17 24.00 0 38 0 1
#> 22.1 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 186.1 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 112 24.00 0 61 0 0
#> 87 24.00 0 27 0 0
#> 102 24.00 0 49 0 0
#> 118 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 143 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 9.2 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 161 24.00 0 45 0 0
#> 17.1 24.00 0 38 0 1
#> 162.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 173.1 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 54.1 24.00 0 53 1 0
#> 193.1 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 198.1 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 165 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 161.1 24.00 0 45 0 0
#> 1.1 24.00 0 23 1 0
#> 144.1 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 116 24.00 0 58 0 1
#> 9.3 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 54.2 24.00 0 53 1 0
#> 87.1 24.00 0 27 0 0
#> 198.2 24.00 0 66 0 1
#> 21 24.00 0 47 0 0
#> 53.1 24.00 0 32 0 1
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 22.2 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 12.1 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 33.2 24.00 0 53 0 0
#> 148.1 24.00 0 61 1 0
#> 112.1 24.00 0 61 0 0
#> 17.2 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 21.1 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 146 24.00 0 63 1 0
#> 161.2 24.00 0 45 0 0
#> 95.1 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 176.1 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.118 NA NA NA
#> 2 age, Cure model -0.000155 NA NA NA
#> 3 grade_ii, Cure model 0.0926 NA NA NA
#> 4 grade_iii, Cure model 0.774 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00615 NA NA NA
#> 2 grade_ii, Survival model 0.629 NA NA NA
#> 3 grade_iii, Survival model 0.153 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1183118 -0.0001554 0.0926059 0.7744831
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 259.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1183117814 -0.0001554406 0.0926059387 0.7744831176
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00615388 0.62925663 0.15335425
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.474076471 0.327084121 0.825137067 0.464128467 0.054678810 0.385078073
#> [7] 0.434575809 0.854767379 0.005331586 0.444498571 0.144256236 0.805099516
#> [13] 0.623944668 0.243858569 0.253177313 0.262431419 0.108751936 0.355512717
#> [19] 0.904378669 0.674434774 0.327084121 0.018861080 0.573767907 0.694734205
#> [25] 0.864715814 0.664273721 0.189836138 0.864715814 0.290257507 0.385078073
#> [31] 0.573767907 0.126194788 0.714899654 0.795094870 0.327084121 0.634016970
#> [37] 0.815142694 0.825137067 0.290257507 0.884528121 0.980921304 0.943282896
#> [43] 0.217016461 0.604042700 0.271769770 0.108751936 0.634016970 0.714899654
#> [49] 0.189836138 0.694734205 0.005331586 0.171965518 0.064087302 0.514011914
#> [55] 0.755246632 0.943282896 0.745087419 0.943282896 0.290257507 0.092000391
#> [61] 0.593877435 0.543884570 0.207951754 0.064087302 0.414876496 0.514011914
#> [67] 0.503943647 0.092000391 0.474076471 0.035137321 0.604042700 0.844840758
#> [73] 0.775079234 0.018861080 0.375163615 0.563733050 0.404955518 0.217016461
#> [79] 0.290257507 0.933522778 0.904378669 0.493898713 0.755246632 0.082176467
#> [85] 0.894479599 0.654130706 0.153635973 0.171965518 0.904378669 0.543884570
#> [91] 0.714899654 0.365314541 0.162887659 0.514011914 0.444498571 0.424702332
#> [97] 0.943282896 0.045275146 0.271769770 0.785107534 0.126194788 0.980921304
#> [103] 0.217016461 0.684620976 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 45 76 107 111 69 51 110 10 24 117 194 56 157
#> 17.42 19.22 11.18 17.45 23.23 18.23 17.56 10.53 23.89 17.46 22.40 12.21 15.10
#> 128 158 166 15 179 183 13 76.1 86 100 155 61 57
#> 20.35 20.14 19.98 22.68 18.63 9.24 14.34 19.22 23.81 16.07 13.08 10.12 14.46
#> 90 61.1 58 51.1 100.1 169 14 42 76.2 180 49 107.1 55
#> 20.94 10.12 19.34 18.23 16.07 22.41 12.89 12.43 19.22 14.82 12.19 11.18 19.34
#> 101 127 25 68 18 170 15.1 180.1 14.1 90.1 155.1 24.1 99
#> 9.97 3.53 6.32 20.62 15.21 19.54 22.68 14.82 12.89 20.94 13.08 23.89 21.19
#> 92 5 154 25.1 140 25.2 55.1 63 26 79 32 92.1 134
#> 22.92 16.43 12.63 6.32 12.68 6.32 19.34 22.77 15.77 16.23 20.90 22.92 17.81
#> 5.1 181 63.1 45.1 164 18.1 159 177 86.1 88 188 40 68.1
#> 16.43 16.46 22.77 17.42 23.60 15.21 10.55 12.53 23.81 18.37 16.16 18.00 20.62
#> 58.1 70 183.1 130 154.1 113 187 96 197 36 183.2 79.1 14.2
#> 19.34 7.38 9.24 16.47 12.63 22.86 9.92 14.54 21.60 21.19 9.24 16.23 12.89
#> 8 153 5.2 117.1 184 25.3 129 170.1 37 169.1 127.1 68.2 60
#> 18.43 21.33 16.43 17.46 17.77 6.32 23.41 19.54 12.52 22.41 3.53 20.62 13.15
#> 83 22 54 95 121 7 33 98 9 193 17 22.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 186.1 9.1 174 112 87 102 118 62 151 162 44 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 35 120 173 9.2 12 161 17.1 162.1 163 163.1 144 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 156 173.1 138 54.1 193.1 1 198.1 19 53 165 176 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 1.1 144.1 2 116 9.3 67 54.2 87.1 198.2 21 53.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 142 22.2 65 83.1 12.1 72 185 33.1 72.1 33.2 148.1 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 174.1 21.1 20 146 161.2 95.1 35.1 182 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004150085 0.773478821 0.442357026
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.04888453 0.02424159 -0.30183059
#> grade_iii, Cure model
#> 0.58370064
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 166 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 179 18.63 1 42 0 0
#> 124 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 113.1 22.86 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 30 17.43 1 78 0 0
#> 113.2 22.86 1 34 0 0
#> 68 20.62 1 44 0 0
#> 4 17.64 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 91 5.33 1 61 0 1
#> 130 16.47 1 53 0 1
#> 37 12.52 1 57 1 0
#> 42.1 12.43 1 49 0 1
#> 125 15.65 1 67 1 0
#> 108 18.29 1 39 0 1
#> 158 20.14 1 74 1 0
#> 108.1 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 25 6.32 1 34 1 0
#> 150.1 20.33 1 48 0 0
#> 42.2 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 90.1 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 195.1 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 30.1 17.43 1 78 0 0
#> 86.1 23.81 1 58 0 1
#> 15 22.68 1 48 0 0
#> 145 10.07 1 65 1 0
#> 52.1 10.42 1 52 0 1
#> 69 23.23 1 25 0 1
#> 42.3 12.43 1 49 0 1
#> 140 12.68 1 59 1 0
#> 90.2 20.94 1 50 0 1
#> 85 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 153 21.33 1 55 1 0
#> 37.1 12.52 1 57 1 0
#> 49 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 23 16.92 1 61 0 0
#> 5 16.43 1 51 0 1
#> 184.1 17.77 1 38 0 0
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 52.2 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 93.1 10.33 1 52 0 1
#> 24.1 23.89 1 38 0 0
#> 107 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 197.1 21.60 1 69 1 0
#> 85.1 16.44 1 36 0 0
#> 61 10.12 1 36 0 1
#> 60.1 13.15 1 38 1 0
#> 133 14.65 1 57 0 0
#> 8.1 18.43 1 32 0 0
#> 70 7.38 1 30 1 0
#> 13 14.34 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 5.1 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 175 21.91 1 43 0 0
#> 155 13.08 1 26 0 0
#> 184.2 17.77 1 38 0 0
#> 164 23.60 1 76 0 1
#> 85.2 16.44 1 36 0 0
#> 129 23.41 1 53 1 0
#> 51.1 18.23 1 83 0 1
#> 129.1 23.41 1 53 1 0
#> 15.1 22.68 1 48 0 0
#> 110 17.56 1 65 0 1
#> 183.1 9.24 1 67 1 0
#> 184.3 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 24.2 23.89 1 38 0 0
#> 90.3 20.94 1 50 0 1
#> 76 19.22 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 37.2 12.52 1 57 1 0
#> 125.1 15.65 1 67 1 0
#> 181 16.46 1 45 0 1
#> 96 14.54 1 33 0 1
#> 91.1 5.33 1 61 0 1
#> 69.1 23.23 1 25 0 1
#> 89 11.44 1 NA 0 0
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 195.2 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 5.2 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 191 24.00 0 60 0 1
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 21 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 47 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 31 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 119 24.00 0 17 0 0
#> 112 24.00 0 61 0 0
#> 135 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 119.1 24.00 0 17 0 0
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 64.1 24.00 0 43 0 0
#> 83.1 24.00 0 6 0 0
#> 80 24.00 0 41 0 0
#> 74.1 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 17.1 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 84 24.00 0 39 0 1
#> 44.1 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 144.1 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 143.2 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 84.1 24.00 0 39 0 1
#> 33 24.00 0 53 0 0
#> 143.3 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 84.2 24.00 0 39 0 1
#> 64.2 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 146.1 24.00 0 63 1 0
#> 44.2 24.00 0 56 0 0
#> 22 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 103.1 24.00 0 56 1 0
#> 20 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 142 24.00 0 53 0 0
#> 182.1 24.00 0 35 0 0
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 137.1 24.00 0 45 1 0
#> 87.1 24.00 0 27 0 0
#> 173.1 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.05 NA NA NA
#> 2 age, Cure model 0.0242 NA NA NA
#> 3 grade_ii, Cure model -0.302 NA NA NA
#> 4 grade_iii, Cure model 0.584 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00415 NA NA NA
#> 2 grade_ii, Survival model 0.773 NA NA NA
#> 3 grade_iii, Survival model 0.442 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.04888 0.02424 -0.30183 0.58370
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 251.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.04888453 0.02424159 -0.30183059 0.58370064
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004150085 0.773478821 0.442357026
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.36534190 0.37497336 0.40404741 0.85369988 0.16387029 0.43303706
#> [7] 0.07876740 0.74154051 0.33653934 0.38465968 0.16387029 0.81153241
#> [13] 0.53701350 0.16387029 0.31751900 0.73245478 0.31751900 0.98439119
#> [19] 0.56566523 0.78584673 0.81153241 0.65959676 0.44282986 0.35575609
#> [25] 0.44282986 0.27051259 0.26022575 0.97652954 0.33653934 0.81153241
#> [31] 0.68682777 0.27051259 0.05283798 0.87057105 0.01638574 0.49039375
#> [37] 0.53701350 0.05283798 0.19537003 0.92016746 0.87057105 0.13138470
#> [43] 0.81153241 0.76814348 0.27051259 0.58479863 0.46192857 0.89536371
#> [49] 0.24982582 0.78584673 0.84521656 0.22883919 0.93658677 0.55603471
#> [55] 0.61315429 0.49039375 0.64117401 0.92839502 0.87057105 0.48094654
#> [61] 0.89536371 0.01638574 0.86216568 0.41374936 0.22883919 0.58479863
#> [67] 0.91189145 0.74154051 0.69597743 0.41374936 0.96075798 0.72338386
#> [73] 0.96075798 0.61315429 0.30795919 0.21742148 0.75923394 0.49039375
#> [79] 0.09370950 0.58479863 0.10834135 0.46192857 0.10834135 0.19537003
#> [85] 0.52751111 0.93658677 0.49039375 0.71428512 0.01638574 0.27051259
#> [91] 0.39438260 0.64117401 0.78584673 0.65959676 0.57525509 0.70515249
#> [97] 0.98439119 0.13138470 0.77698162 0.95271851 0.15291892 0.61315429
#> [103] 0.67769544 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 166 105 179 43 113 88 168 60 150 58 113.1 42 30
#> 19.98 19.75 18.63 12.10 22.86 18.37 23.72 13.15 20.33 19.34 22.86 12.43 17.43
#> 113.2 68 81 68.1 91 130 37 42.1 125 108 158 108.1 90
#> 22.86 20.62 14.06 20.62 5.33 16.47 12.52 12.43 15.65 18.29 20.14 18.29 20.94
#> 36 25 150.1 42.2 180 90.1 86 52 24 184 30.1 86.1 15
#> 21.19 6.32 20.33 12.43 14.82 20.94 23.81 10.42 23.89 17.77 17.43 23.81 22.68
#> 145 52.1 69 42.3 140 90.2 85 51 93 153 37.1 49 197
#> 10.07 10.42 23.23 12.43 12.68 20.94 16.44 18.23 10.33 21.33 12.52 12.19 21.60
#> 183 23 5 184.1 79 101 52.2 41 93.1 24.1 107 8 197.1
#> 9.24 16.92 16.43 17.77 16.23 9.97 10.42 18.02 10.33 23.89 11.18 18.43 21.60
#> 85.1 61 60.1 133 8.1 70 13 70.1 5.1 32 175 155 184.2
#> 16.44 10.12 13.15 14.65 18.43 7.38 14.34 7.38 16.43 20.90 21.91 13.08 17.77
#> 164 85.2 129 51.1 129.1 15.1 110 183.1 184.3 57 24.2 90.3 76
#> 23.60 16.44 23.41 18.23 23.41 22.68 17.56 9.24 17.77 14.46 23.89 20.94 19.22
#> 79.1 37.2 125.1 181 96 91.1 69.1 177 149 92 5.2 157 54
#> 16.23 12.52 15.65 16.46 14.54 5.33 23.23 12.53 8.37 22.92 16.43 15.10 24.00
#> 82 191 147 44 21 95 143 27 144 2 47 64 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 143.1 160 193 71 132 7 31 147.1 48 200 65 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 74 161 119 112 135 87 162 118 141 71.1 156 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 83 146 116 64.1 83.1 80 74.1 35 163 193.1 17.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 84 44.1 196 144.1 3 143.2 138 178.1 75 185 119.2 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 143.3 103 84.2 64.2 173 146.1 44.2 22 137 1 103.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 142 182.1 12 34 137.1 87.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006428589 0.360092462 0.296470182
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06362504 0.02233633 -0.29368270
#> grade_iii, Cure model
#> 1.00315202
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 136 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 8 18.43 1 32 0 0
#> 105 19.75 1 60 0 0
#> 77 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 10 10.53 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 85 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 91 5.33 1 61 0 1
#> 49 12.19 1 48 1 0
#> 136.1 21.83 1 43 0 1
#> 86 23.81 1 58 0 1
#> 167 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 13 14.34 1 54 0 1
#> 52 10.42 1 52 0 1
#> 32 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 90 20.94 1 50 0 1
#> 101 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 197 21.60 1 69 1 0
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 130 16.47 1 53 0 1
#> 81.1 14.06 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 55 19.34 1 69 0 1
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 195 11.76 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 10.2 10.53 1 34 0 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 129 23.41 1 53 1 0
#> 166 19.98 1 48 0 0
#> 42 12.43 1 49 0 1
#> 63 22.77 1 31 1 0
#> 164 23.60 1 76 0 1
#> 26 15.77 1 49 0 1
#> 179 18.63 1 42 0 0
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 15 22.68 1 48 0 0
#> 184 17.77 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 29 15.45 1 68 1 0
#> 101.1 9.97 1 10 0 1
#> 57 14.46 1 45 0 1
#> 77.1 7.27 1 67 0 1
#> 164.1 23.60 1 76 0 1
#> 57.1 14.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 100 16.07 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 23.1 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 43 12.10 1 61 0 1
#> 100.1 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 127.1 3.53 1 62 0 1
#> 69 23.23 1 25 0 1
#> 139.1 21.49 1 63 1 0
#> 51 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 43.1 12.10 1 61 0 1
#> 111.1 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 157 15.10 1 47 0 0
#> 88 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 93.1 10.33 1 52 0 1
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 24 23.89 1 38 0 0
#> 180 14.82 1 37 0 0
#> 96 14.54 1 33 0 1
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 6 15.64 1 39 0 0
#> 154 12.63 1 20 1 0
#> 96.1 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 127.2 3.53 1 62 0 1
#> 93.2 10.33 1 52 0 1
#> 117.1 17.46 1 26 0 1
#> 58.1 19.34 1 39 0 0
#> 49.1 12.19 1 48 1 0
#> 117.2 17.46 1 26 0 1
#> 145.1 10.07 1 65 1 0
#> 169 22.41 1 46 0 0
#> 36 21.19 1 48 0 1
#> 100.2 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 86.1 23.81 1 58 0 1
#> 179.1 18.63 1 42 0 0
#> 136.2 21.83 1 43 0 1
#> 15.1 22.68 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 36.1 21.19 1 48 0 1
#> 26.1 15.77 1 49 0 1
#> 158 20.14 1 74 1 0
#> 137 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 102.1 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 48 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 27 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 178.1 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 156.1 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 116.1 24.00 0 58 0 1
#> 7.1 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 2.1 24.00 0 9 0 0
#> 48.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 82.1 24.00 0 34 0 0
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 172.1 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 143 24.00 0 51 0 0
#> 116.2 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 126 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 116.3 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#> 46.1 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 196 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 28 24.00 0 67 1 0
#> 46.2 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 144 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 53.1 24.00 0 32 0 1
#> 65 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 7.2 24.00 0 37 1 0
#> 1.1 24.00 0 23 1 0
#> 193.2 24.00 0 45 0 1
#> 135.1 24.00 0 58 1 0
#> 87 24.00 0 27 0 0
#> 151.1 24.00 0 42 0 0
#> 146.1 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 172.2 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 173.2 24.00 0 19 0 1
#> 87.1 24.00 0 27 0 0
#> 165 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 11.1 24.00 0 42 0 1
#> 193.3 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0223 NA NA NA
#> 3 grade_ii, Cure model -0.294 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00643 NA NA NA
#> 2 grade_ii, Survival model 0.360 NA NA NA
#> 3 grade_iii, Survival model 0.296 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06363 0.02234 -0.29368 1.00315
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 247.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06362504 0.02233633 -0.29368270 1.00315202
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006428589 0.360092462 0.296470182
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.130335223 0.718041808 0.327296740 0.262885830 0.939568767 0.657878921
#> [7] 0.788263117 0.788263117 0.470587127 0.858770784 0.959703521 0.728129944
#> [13] 0.130335223 0.017383404 0.548422989 0.103941393 0.637926415 0.627932791
#> [19] 0.818399328 0.226861029 0.356141431 0.209146102 0.879047805 0.828575315
#> [25] 0.155761302 0.768193773 0.687919023 0.460882306 0.637926415 0.209146102
#> [31] 0.272067597 0.009087525 0.422773088 0.164786649 0.299209314 0.788263117
#> [37] 0.365789446 0.441694333 0.046576658 0.253805582 0.707998830 0.071276677
#> [43] 0.031333127 0.518900902 0.308578231 0.182427275 0.899203342 0.079296323
#> [49] 0.375387524 0.697958469 0.558351146 0.879047805 0.608120055 0.939568767
#> [55] 0.031333127 0.608120055 0.470587127 0.489809348 0.103941393 0.121207419
#> [61] 0.969834012 0.441694333 0.272067597 0.748137375 0.489809348 0.929474199
#> [67] 0.969834012 0.054926111 0.164786649 0.346465009 0.063097657 0.748137375
#> [73] 0.422773088 0.768193773 0.568292415 0.336845313 0.394718417 0.828575315
#> [79] 0.909355141 0.909355141 0.002534997 0.578279245 0.588302721 0.667913162
#> [85] 0.385039097 0.538494821 0.677935316 0.588302721 0.969834012 0.828575315
#> [91] 0.394718417 0.272067597 0.728129944 0.394718417 0.858770784 0.095350523
#> [97] 0.191468957 0.489809348 0.235851990 0.017383404 0.308578231 0.130335223
#> [103] 0.079296323 0.191468957 0.518900902 0.244810799 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 136 56 8 105 77 60 10 10.1 85 145 91 49 136.1
#> 21.83 12.21 18.43 19.75 7.27 13.15 10.53 10.53 16.44 10.07 5.33 12.19 21.83
#> 86 167 66 81 13 52 32 41 90 101 93 197 159
#> 23.81 15.55 22.13 14.06 14.34 10.42 20.90 18.02 20.94 9.97 10.33 21.60 10.55
#> 177 130 81.1 90.1 55 78 111 139 97 10.2 40 23 129
#> 12.53 16.47 14.06 20.94 19.34 23.88 17.45 21.49 19.14 10.53 18.00 16.92 23.41
#> 166 42 63 164 26 179 153 16 15 184 37 29 101.1
#> 19.98 12.43 22.77 23.60 15.77 18.63 21.33 8.71 22.68 17.77 12.52 15.45 9.97
#> 57 77.1 164.1 57.1 192 100 66.1 175 127 23.1 58 43 100.1
#> 14.46 7.27 23.60 14.46 16.44 16.07 22.13 21.91 3.53 16.92 19.34 12.10 16.07
#> 70 127.1 69 139.1 51 92 43.1 111.1 159.1 157 88 117 93.1
#> 7.38 3.53 23.23 21.49 18.23 22.92 12.10 17.45 10.55 15.10 18.37 17.46 10.33
#> 149 149.1 24 180 96 123 110 6 154 96.1 127.2 93.2 117.1
#> 8.37 8.37 23.89 14.82 14.54 13.00 17.56 15.64 12.63 14.54 3.53 10.33 17.46
#> 58.1 49.1 117.2 145.1 169 36 100.2 190 86.1 179.1 136.2 15.1 36.1
#> 19.34 12.19 17.46 10.07 22.41 21.19 16.07 20.81 23.81 18.63 21.83 22.68 21.19
#> 26.1 158 137 118 20 34 102 80 160 31 3 156 46
#> 15.77 20.14 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 122 178 7 2 53 102.1 104 48 186 82 27 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 185 151 156.1 173 67 193 146 116.1 7.1 142 2.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 82.1 121 172 172.1 83 143 116.2 109 126 12 103 116.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 132 46.1 135 196 193.1 71 173.1 28 46.2 98 144 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 65 122.1 7.2 1.1 193.2 135.1 87 151.1 146.1 104.1 65.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 172.2 141 173.2 87.1 165 103.1 162 80.1 11.1 193.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01368079 0.46433383 0.33236667
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.79551947 0.01816845 -0.10190576
#> grade_iii, Cure model
#> 0.53440364
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 100 16.07 1 60 0 0
#> 107 11.18 1 54 1 0
#> 170 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 189 10.51 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 59 10.16 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 39 15.59 1 37 0 1
#> 6 15.64 1 39 0 0
#> 89 11.44 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 57.1 14.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 171 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 16.1 8.71 1 71 0 1
#> 107.1 11.18 1 54 1 0
#> 57.2 14.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 69 23.23 1 25 0 1
#> 175.1 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 8 18.43 1 32 0 0
#> 167 15.55 1 56 1 0
#> 61 10.12 1 36 0 1
#> 37 12.52 1 57 1 0
#> 99 21.19 1 38 0 1
#> 32 20.90 1 37 1 0
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 56 12.21 1 60 0 0
#> 6.1 15.64 1 39 0 0
#> 158 20.14 1 74 1 0
#> 113 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 88 18.37 1 47 0 0
#> 123 13.00 1 44 1 0
#> 86.1 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 59.2 10.16 1 NA 1 0
#> 175.2 21.91 1 43 0 0
#> 85 16.44 1 36 0 0
#> 59.3 10.16 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 145 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 29 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 130 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 192.1 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 77 7.27 1 67 0 1
#> 134 17.81 1 47 1 0
#> 133 14.65 1 57 0 0
#> 170.1 19.54 1 43 0 1
#> 24 23.89 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 99.1 21.19 1 38 0 1
#> 187 9.92 1 39 1 0
#> 55 19.34 1 69 0 1
#> 130.1 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 79 16.23 1 54 1 0
#> 68.2 20.62 1 44 0 0
#> 63 22.77 1 31 1 0
#> 39.1 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 43.1 12.10 1 61 0 1
#> 100.1 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 15.1 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 175.3 21.91 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 10 10.53 1 34 0 0
#> 128 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 26.1 15.77 1 49 0 1
#> 63.1 22.77 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 175.4 21.91 1 43 0 0
#> 69.1 23.23 1 25 0 1
#> 85.1 16.44 1 36 0 0
#> 36 21.19 1 48 0 1
#> 52 10.42 1 52 0 1
#> 79.1 16.23 1 54 1 0
#> 184.1 17.77 1 38 0 0
#> 190 20.81 1 42 1 0
#> 66 22.13 1 53 0 0
#> 100.2 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 25.1 6.32 1 34 1 0
#> 158.1 20.14 1 74 1 0
#> 189.1 10.51 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 109 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 48 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 173.1 24.00 0 19 0 1
#> 31 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 176.1 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 109.1 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 173.2 24.00 0 19 0 1
#> 82 24.00 0 34 0 0
#> 198.2 24.00 0 66 0 1
#> 141.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 176.2 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 172.1 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 115 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 46 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 118 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 27.1 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 80.1 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 144.1 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 98.1 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 126 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 73 24.00 0 NA 0 1
#> 185.2 24.00 0 44 1 0
#> 142.2 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 126.1 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 142.3 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 9.1 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 46.1 24.00 0 71 0 0
#> 31.2 24.00 0 36 0 1
#> 185.3 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.796 NA NA NA
#> 2 age, Cure model 0.0182 NA NA NA
#> 3 grade_ii, Cure model -0.102 NA NA NA
#> 4 grade_iii, Cure model 0.534 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0137 NA NA NA
#> 2 grade_ii, Survival model 0.464 NA NA NA
#> 3 grade_iii, Survival model 0.332 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79552 0.01817 -0.10191 0.53440
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 250.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.79551947 0.01816845 -0.10190576 0.53440364
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01368079 0.46433383 0.33236667
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7907941 0.9263936 0.6296711 0.4198853 0.1932241 0.9644490 0.8606825
#> [8] 0.5391894 0.8294857 0.8186009 0.8898842 0.9726168 0.8606825 0.4964042
#> [15] 0.8802239 0.7300023 0.9884356 0.9726168 0.9263936 0.8606825 0.8753573
#> [22] 0.6451953 0.2493130 0.4198853 0.8946235 0.6747647 0.8401862 0.9520375
#> [29] 0.9039016 0.5080632 0.5494172 0.6962302 0.6601288 0.7732133 0.7491030
#> [36] 0.5689555 0.9084942 0.8186009 0.6052364 0.2954759 0.9350215 0.6820085
#> [43] 0.8850792 0.1932241 0.9478301 0.4198853 0.7491030 0.9520375 0.9603399
#> [50] 0.9175741 0.8946235 0.8454717 0.3553589 0.7365274 0.5689555 0.7491030
#> [57] 0.9130575 0.9845175 0.7031830 0.8556259 0.6296711 0.1066181 0.5080632
#> [64] 0.9685477 0.6451953 0.7365274 0.6215564 0.7792272 0.5689555 0.3184315
#> [71] 0.8294857 0.8076131 0.9175741 0.7907941 0.6674779 0.3553589 0.9961626
#> [78] 0.4198853 0.8454717 0.6891835 0.9393106 0.5961910 0.4839349 0.7233919
#> [85] 0.8076131 0.3184315 0.7099993 0.4198853 0.2493130 0.7491030 0.5080632
#> [92] 0.9435880 0.7792272 0.7099993 0.5593421 0.3890424 0.7907941 0.9805602
#> [99] 0.9884356 0.6052364 0.3890424 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 100 107 170 175 86 101 57 90 39 6 140 16 57.1
#> 16.07 11.18 19.54 21.91 23.81 9.97 14.46 20.94 15.59 15.64 12.68 8.71 14.46
#> 139 155 171 25 16.1 107.1 57.2 13 58 69 175.1 177 8
#> 21.49 13.08 16.57 6.32 8.71 11.18 14.46 14.34 19.34 23.23 21.91 12.53 18.43
#> 167 61 37 99 32 40 76 5 192 68 56 6.1 158
#> 15.55 10.12 12.52 21.19 20.90 18.00 19.22 16.43 16.44 20.62 12.21 15.64 20.14
#> 113 159 88 123 86.1 93 175.2 85 61.1 145 43 177.1 29
#> 22.86 10.55 18.37 13.00 23.81 10.33 21.91 16.44 10.12 10.07 12.10 12.53 15.45
#> 15 130 68.1 192.1 49 77 134 133 170.1 24 99.1 187 55
#> 22.68 16.47 20.62 16.44 12.19 7.27 17.81 14.65 19.54 23.89 21.19 9.92 19.34
#> 130.1 166 79 68.2 63 39.1 26 43.1 100.1 179 15.1 127 175.3
#> 16.47 19.98 16.23 20.62 22.77 15.59 15.77 12.10 16.07 18.63 22.68 3.53 21.91
#> 29.1 41 10 128 197 30 26.1 63.1 184 175.4 69.1 85.1 36
#> 15.45 18.02 10.53 20.35 21.60 17.43 15.77 22.77 17.77 21.91 23.23 16.44 21.19
#> 52 79.1 184.1 190 66 100.2 70 25.1 158.1 66.1 109 20 156
#> 10.42 16.23 17.77 20.81 22.13 16.07 7.38 6.32 20.14 22.13 24.00 24.00 24.00
#> 185 44 48 176 27 165 198 173 141 17 9 163 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 173.1 31 38 143 185.1 176.1 151 7 67 75 19 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 198.1 109.1 120 173.2 82 198.2 141.1 71 137 35 65 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.2 22 172 172.1 22.1 148 98 46 163.1 151.1 118 135 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 80 142 31.1 182 83 152 75.1 80.1 138 144 144.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 84 98.1 178 126 12 185.2 142.2 1 126.1 143.1 142.3 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 46.1 31.2 185.3
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.000899272 0.347099290 0.296119305
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.455076844 0.002447296 -0.084445013
#> grade_iii, Cure model
#> 1.567619463
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 16 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 50 10.02 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 194 22.40 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 92 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 42 12.43 1 49 0 1
#> 117 17.46 1 26 0 1
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 37.1 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 23 16.92 1 61 0 0
#> 68 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 91 5.33 1 61 0 1
#> 78 23.88 1 43 0 0
#> 30 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 57 14.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 81.1 14.06 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 63 22.77 1 31 1 0
#> 149 8.37 1 33 1 0
#> 181.1 16.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 199.2 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 158 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 86 23.81 1 58 0 1
#> 13.1 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 179 18.63 1 42 0 0
#> 124 9.73 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 13.2 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 136 21.83 1 43 0 1
#> 192.1 16.44 1 31 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 61 10.12 1 36 0 1
#> 81.2 14.06 1 34 0 0
#> 59.1 10.16 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 90.1 20.94 1 50 0 1
#> 159.1 10.55 1 50 0 1
#> 180 14.82 1 37 0 0
#> 69.1 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 37.2 12.52 1 57 1 0
#> 153 21.33 1 55 1 0
#> 110.1 17.56 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 175 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 184.1 17.77 1 38 0 0
#> 139 21.49 1 63 1 0
#> 181.2 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 81.3 14.06 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 78.2 23.88 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 43.1 12.10 1 61 0 1
#> 183 9.24 1 67 1 0
#> 181.3 16.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 59.2 10.16 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 195.1 11.76 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 170 19.54 1 43 0 1
#> 124.1 9.73 1 NA 1 0
#> 81.4 14.06 1 34 0 0
#> 139.1 21.49 1 63 1 0
#> 8 18.43 1 32 0 0
#> 164.1 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 69.2 23.23 1 25 0 1
#> 52 10.42 1 52 0 1
#> 97.1 19.14 1 65 0 1
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 57.2 14.46 1 45 0 1
#> 184.2 17.77 1 38 0 0
#> 163 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 131 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 198 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 122.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 131.1 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 146 24.00 0 63 1 0
#> 65 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 178.1 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 126 24.00 0 48 0 0
#> 182.1 24.00 0 35 0 0
#> 65.1 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 119 24.00 0 17 0 0
#> 102.1 24.00 0 49 0 0
#> 118.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 109.1 24.00 0 48 0 0
#> 102.2 24.00 0 49 0 0
#> 19 24.00 0 57 0 1
#> 109.2 24.00 0 48 0 0
#> 119.1 24.00 0 17 0 0
#> 120 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 2.1 24.00 0 9 0 0
#> 71 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 118.2 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 87.1 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 191 24.00 0 60 0 1
#> 38.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 62 24.00 0 71 0 0
#> 109.3 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 182.2 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 118.3 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 65.2 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 47 24.00 0 38 0 1
#> 65.3 24.00 0 57 1 0
#> 20.1 24.00 0 46 1 0
#> 65.4 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 122.2 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 165.1 24.00 0 47 0 0
#> 185.1 24.00 0 44 1 0
#> 191.1 24.00 0 60 0 1
#> 54.1 24.00 0 53 1 0
#> 191.2 24.00 0 60 0 1
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 38.2 24.00 0 31 1 0
#> 54.2 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.455 NA NA NA
#> 2 age, Cure model 0.00245 NA NA NA
#> 3 grade_ii, Cure model -0.0844 NA NA NA
#> 4 grade_iii, Cure model 1.57 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000899 NA NA NA
#> 2 grade_ii, Survival model 0.347 NA NA NA
#> 3 grade_iii, Survival model 0.296 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.455077 0.002447 -0.084445 1.567619
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.8
#> Residual Deviance: 232.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.455076844 0.002447296 -0.084445013 1.567619463
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.000899272 0.347099290 0.296119305
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79899998 0.94535265 0.70628968 0.32690328 0.33761776 0.59222744
#> [7] 0.25992592 0.22271289 0.46886243 0.19678119 0.67164361 0.14374344
#> [13] 0.73170709 0.82382838 0.52648248 0.57383326 0.57383326 0.79899998
#> [19] 0.84858688 0.55497795 0.34817500 0.85680426 0.11344519 0.97679206
#> [25] 0.04603554 0.54551009 0.50743118 0.68049033 0.83215483 0.73170709
#> [31] 0.92155295 0.15896797 0.30550643 0.20992899 0.95325626 0.59222744
#> [37] 0.40962345 0.04603554 0.87303430 0.53603028 0.87303430 0.38933140
#> [43] 0.77350342 0.47866919 0.09480061 0.70628968 0.42978017 0.35871937
#> [49] 0.44922508 0.65393390 0.70628968 0.62758027 0.24769347 0.62758027
#> [55] 0.56443671 0.89737223 0.90545956 0.73170709 0.99226079 0.30550643
#> [61] 0.85680426 0.66279075 0.15896797 0.62758027 0.79899998 0.29428905
#> [67] 0.50743118 0.97679206 0.23521618 0.79050610 0.47866919 0.27187426
#> [73] 0.59222744 0.68049033 0.01751414 0.73170709 0.35871937 0.04603554
#> [79] 0.91351890 0.83215483 0.92955453 0.59222744 0.96112999 0.92955453
#> [85] 0.37904228 0.41974991 0.73170709 0.27187426 0.45904681 0.11344519
#> [91] 0.78200585 0.15896797 0.88925498 0.42978017 0.39948310 0.96897458
#> [97] 0.68049033 0.47866919 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 37 16 13 32 190 181 197 194 88 92 133 129 81
#> 12.52 8.71 14.34 20.90 20.81 16.46 21.60 22.40 18.37 22.92 14.65 23.41 14.06
#> 42 117 130 130.1 37.1 107 23 68 159 164 91 78 30
#> 12.43 17.46 16.47 16.47 12.52 11.18 16.92 20.62 10.55 23.60 5.33 23.88 17.43
#> 110 57 43 81.1 187 69 90 63 149 181.1 105 78.1 10
#> 17.56 14.46 12.10 14.06 9.92 23.23 20.94 22.77 8.37 16.46 19.75 23.88 10.53
#> 111 10.1 158 60 184 86 13.1 97 128 179 188 13.2 192
#> 17.45 10.53 20.14 13.15 17.77 23.81 14.34 19.14 20.35 18.63 16.16 14.34 16.44
#> 136 192.1 171 93 61 81.2 127 90.1 159.1 180 69.1 85 37.2
#> 21.83 16.44 16.57 10.33 10.12 14.06 3.53 20.94 10.55 14.82 23.23 16.44 12.52
#> 153 110.1 91.1 175 177 184.1 139 181.2 57.1 24 81.3 128.1 78.2
#> 21.33 17.56 5.33 21.91 12.53 17.77 21.49 16.46 14.46 23.89 14.06 20.35 23.88
#> 101 43.1 183 181.3 70 183.1 150 170 81.4 139.1 8 164.1 155
#> 9.97 12.10 9.24 16.46 7.38 9.24 20.33 19.54 14.06 21.49 18.43 23.60 13.08
#> 69.2 52 97.1 166 77 57.2 184.2 163 38 64 172 118 182
#> 23.23 10.42 19.14 19.98 7.27 14.46 17.77 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 122 2 142 12 198 196 121 53 122.1 1 131.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 65 178 165 109 144 178.1 102 126 182.1 65.1 151 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 118.1 174 109.1 102.2 19 109.2 119.1 120 193 35 185 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 2.1 71 151.1 118.2 135 87.1 141 54 191 38.1 33 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 109.3 173 182.2 84 176 118.3 147 65.2 21 112 20 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.3 20.1 65.4 80 94 122.2 165.1 185.1 191.1 54.1 191.2 98 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 38.2 54.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01357167 0.96414671 0.55377533
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.66817125 0.01692842 -0.53438151
#> grade_iii, Cure model
#> 0.57240781
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 15 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 133 14.65 1 57 0 0
#> 93 10.33 1 52 0 1
#> 117 17.46 1 26 0 1
#> 59 10.16 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 23 16.92 1 61 0 0
#> 86.1 23.81 1 58 0 1
#> 91.1 5.33 1 61 0 1
#> 45 17.42 1 54 0 1
#> 166 19.98 1 48 0 0
#> 101 9.97 1 10 0 1
#> 134 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 134.1 17.81 1 47 1 0
#> 124.1 9.73 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 86.2 23.81 1 58 0 1
#> 25 6.32 1 34 1 0
#> 194 22.40 1 38 0 1
#> 153 21.33 1 55 1 0
#> 124.2 9.73 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 145 10.07 1 65 1 0
#> 93.1 10.33 1 52 0 1
#> 30 17.43 1 78 0 0
#> 150 20.33 1 48 0 0
#> 155 13.08 1 26 0 0
#> 187 9.92 1 39 1 0
#> 167 15.55 1 56 1 0
#> 37 12.52 1 57 1 0
#> 30.1 17.43 1 78 0 0
#> 169 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 154 12.63 1 20 1 0
#> 111 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 59.1 10.16 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 37.1 12.52 1 57 1 0
#> 136 21.83 1 43 0 1
#> 155.1 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 50 10.02 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 23.1 16.92 1 61 0 0
#> 123 13.00 1 44 1 0
#> 128 20.35 1 35 0 1
#> 29 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 170 19.54 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 15.1 22.68 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 101.1 9.97 1 10 0 1
#> 150.1 20.33 1 48 0 0
#> 140 12.68 1 59 1 0
#> 77.1 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 50.1 10.02 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 130 16.47 1 53 0 1
#> 105 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 99.1 21.19 1 38 0 1
#> 85.1 16.44 1 36 0 0
#> 68.1 20.62 1 44 0 0
#> 188 16.16 1 46 0 1
#> 37.2 12.52 1 57 1 0
#> 60.2 13.15 1 38 1 0
#> 114 13.68 1 NA 0 0
#> 93.2 10.33 1 52 0 1
#> 101.2 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 50.2 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 106 16.67 1 49 1 0
#> 8 18.43 1 32 0 0
#> 88 18.37 1 47 0 0
#> 24 23.89 1 38 0 0
#> 113 22.86 1 34 0 0
#> 180 14.82 1 37 0 0
#> 125 15.65 1 67 1 0
#> 166.1 19.98 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 96.1 14.54 1 33 0 1
#> 110.1 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 136.1 21.83 1 43 0 1
#> 96.2 14.54 1 33 0 1
#> 58 19.34 1 39 0 0
#> 60.3 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 17 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 53.1 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 87 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 174 24.00 0 49 1 0
#> 19 24.00 0 57 0 1
#> 53.2 24.00 0 32 0 1
#> 137 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 19.1 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 48.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 137.1 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 162.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 72 24.00 0 40 0 1
#> 132 24.00 0 55 0 0
#> 65 24.00 0 57 1 0
#> 118.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 83 24.00 0 6 0 0
#> 186 24.00 0 45 1 0
#> 12.1 24.00 0 63 0 0
#> 103.1 24.00 0 56 1 0
#> 82.1 24.00 0 34 0 0
#> 176 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 3.1 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 28 24.00 0 67 1 0
#> 141 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 87.2 24.00 0 27 0 0
#> 31 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 3.2 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 20.2 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 19.2 24.00 0 57 0 1
#> 74.2 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 82.2 24.00 0 34 0 0
#> 64 24.00 0 43 0 0
#> 74.3 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 7.1 24.00 0 37 1 0
#> 152 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 178.1 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.668 NA NA NA
#> 2 age, Cure model 0.0169 NA NA NA
#> 3 grade_ii, Cure model -0.534 NA NA NA
#> 4 grade_iii, Cure model 0.572 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0136 NA NA NA
#> 2 grade_ii, Survival model 0.964 NA NA NA
#> 3 grade_iii, Survival model 0.554 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66817 0.01693 -0.53438 0.57241
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 246.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66817125 0.01692842 -0.53438151 0.57240781
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01357167 0.96414671 0.55377533
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0365599537 0.9782808108 0.5787386933 0.8144150598 0.3403440875
#> [6] 0.6368129702 0.4399168952 0.3192924635 0.9133882935 0.0105629294
#> [11] 0.5905506746 0.9566815150 0.2674474835 0.4513396742 0.3945274259
#> [16] 0.0105629294 0.9566815150 0.3834132741 0.1895538377 0.8699992718
#> [21] 0.2884013055 0.1805220543 0.2884013055 0.4743405763 0.0105629294
#> [26] 0.9351985162 0.0574016039 0.1061813076 0.4743405763 0.8588097993
#> [31] 0.8144150598 0.3616092910 0.1629442606 0.6807682233 0.9024955966
#> [36] 0.5438664476 0.7484059491 0.3616092910 0.0497769511 0.7921307574
#> [41] 0.0044438601 0.7372701871 0.3509636877 0.0977385286 0.8476078587
#> [46] 0.7484059491 0.0815456117 0.6807682233 0.9351985162 0.4974867168
#> [51] 0.3945274259 0.7033327982 0.1543613058 0.5554658982 0.1144643249
#> [56] 0.2176967745 0.6368129702 0.0365599537 0.2674474835 0.8699992718
#> [61] 0.1629442606 0.7259638079 0.9133882935 0.1375986893 0.3087846554
#> [66] 0.0649887116 0.0247069408 0.2273966925 0.4285105277 0.2080096015
#> [71] 0.1144643249 0.7146260854 0.1144643249 0.4513396742 0.1375986893
#> [76] 0.5091263446 0.7484059491 0.6368129702 0.8144150598 0.8699992718
#> [81] 0.7810178264 0.8032620138 0.4171503055 0.2469793042 0.2571173386
#> [86] 0.0008324962 0.0304191777 0.5670551605 0.5322107124 0.1895538377
#> [91] 0.9782808108 0.5905506746 0.3192924635 0.0730596568 0.0815456117
#> [96] 0.5905506746 0.2273966925 0.6368129702 0.6250564878 0.5091263446
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 15 127 133 93 117 60 181 110 77 86 96 91 51
#> 22.68 3.53 14.65 10.33 17.46 13.15 16.46 17.56 7.27 23.81 14.54 5.33 18.23
#> 85 23 86.1 91.1 45 166 101 134 158 134.1 5 86.2 25
#> 16.44 16.92 23.81 5.33 17.42 19.98 9.97 17.81 20.14 17.81 16.43 23.81 6.32
#> 194 153 5.1 145 93.1 30 150 155 187 167 37 30.1 169
#> 22.40 21.33 16.43 10.07 10.33 17.43 20.33 13.08 9.92 15.55 12.52 17.43 22.41
#> 159 78 154 111 197 61 37.1 136 155.1 25.1 79 23.1 123
#> 10.55 23.88 12.63 17.45 21.60 10.12 12.52 21.83 13.08 6.32 16.23 16.92 13.00
#> 128 29 99 170 60.1 15.1 51.1 101.1 150.1 140 77.1 68 184
#> 20.35 15.45 21.19 19.54 13.15 22.68 18.23 9.97 20.33 12.68 7.27 20.62 17.77
#> 66 129 55 130 105 36 14 99.1 85.1 68.1 188 37.2 60.2
#> 22.13 23.41 19.34 16.47 19.75 21.19 12.89 21.19 16.44 20.62 16.16 12.52 13.15
#> 93.2 101.2 56 52 106 8 88 24 113 180 125 166.1 127.1
#> 10.33 9.97 12.21 10.42 16.67 18.43 18.37 23.89 22.86 14.82 15.65 19.98 3.53
#> 96.1 110.1 175 136.1 96.2 58 60.3 13 188.1 17 165 53 53.1
#> 14.54 17.56 21.91 21.83 14.54 19.34 13.15 14.34 16.16 24.00 24.00 24.00 24.00
#> 172 142 3 74 94 87 142.1 84 82 48 20 20.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 103 174 19 53.2 137 46 162 126 19.1 7 48.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 138 22 21 95 147 137.1 118 27 185 87.1 162.1 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 132 65 118.1 12 104 11 83 186 12.1 103.1 82.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 3.1 2 28 141 46.1 120 80 87.2 31 148 3.2 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 1 19.2 74.2 163 38.1 146 82.2 64 74.3 109 7.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 178.1 141.1 165.1 152.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02156463 0.60990729 0.45334879
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76518109 0.01369916 0.08281942
#> grade_iii, Cure model
#> 0.89876461
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 43 12.10 1 61 0 1
#> 195 11.76 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 149 8.37 1 33 1 0
#> 124 9.73 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 37 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 113 22.86 1 34 0 0
#> 183 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 36 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 24 23.89 1 38 0 0
#> 55 19.34 1 69 0 1
#> 159 10.55 1 50 0 1
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 159.1 10.55 1 50 0 1
#> 179 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 55.1 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 23 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 159.2 10.55 1 50 0 1
#> 136 21.83 1 43 0 1
#> 111 17.45 1 47 0 1
#> 158 20.14 1 74 1 0
#> 181 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 42.1 12.43 1 49 0 1
#> 23.1 16.92 1 61 0 0
#> 167 15.55 1 56 1 0
#> 128 20.35 1 35 0 1
#> 155.1 13.08 1 26 0 0
#> 16 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 149.1 8.37 1 33 1 0
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 97 19.14 1 65 0 1
#> 32 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 125 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 133 14.65 1 57 0 0
#> 125.1 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 128.1 20.35 1 35 0 1
#> 41.1 18.02 1 40 1 0
#> 15 22.68 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 63.1 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 171 16.57 1 41 0 1
#> 195.1 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 90 20.94 1 50 0 1
#> 6 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 40 18.00 1 28 1 0
#> 88.1 18.37 1 47 0 0
#> 37.1 12.52 1 57 1 0
#> 61 10.12 1 36 0 1
#> 30 17.43 1 78 0 0
#> 92 22.92 1 47 0 1
#> 77 7.27 1 67 0 1
#> 108 18.29 1 39 0 1
#> 177 12.53 1 75 0 0
#> 187 9.92 1 39 1 0
#> 88.2 18.37 1 47 0 0
#> 184 17.77 1 38 0 0
#> 68.1 20.62 1 44 0 0
#> 96.1 14.54 1 33 0 1
#> 49 12.19 1 48 1 0
#> 117 17.46 1 26 0 1
#> 78.1 23.88 1 43 0 0
#> 124.1 9.73 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 183.1 9.24 1 67 1 0
#> 96.2 14.54 1 33 0 1
#> 127.1 3.53 1 62 0 1
#> 190 20.81 1 42 1 0
#> 171.1 16.57 1 41 0 1
#> 96.3 14.54 1 33 0 1
#> 39 15.59 1 37 0 1
#> 81 14.06 1 34 0 0
#> 51 18.23 1 83 0 1
#> 167.1 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 188.1 16.16 1 46 0 1
#> 190.1 20.81 1 42 1 0
#> 107.2 11.18 1 54 1 0
#> 81.1 14.06 1 34 0 0
#> 69.1 23.23 1 25 0 1
#> 69.2 23.23 1 25 0 1
#> 199 19.81 1 NA 0 1
#> 90.1 20.94 1 50 0 1
#> 69.3 23.23 1 25 0 1
#> 15.1 22.68 1 48 0 0
#> 100 16.07 1 60 0 0
#> 63.2 22.77 1 31 1 0
#> 167.2 15.55 1 56 1 0
#> 87 24.00 0 27 0 0
#> 71 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 174 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 174.1 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 87.1 24.00 0 27 0 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 95 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 82 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 53.1 24.00 0 32 0 1
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 20.1 24.00 0 46 1 0
#> 118 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 156 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 38.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 53.2 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 2.1 24.00 0 9 0 0
#> 44 24.00 0 56 0 0
#> 83.1 24.00 0 6 0 0
#> 121 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 7 24.00 0 37 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 193.1 24.00 0 45 0 1
#> 173.1 24.00 0 19 0 1
#> 82.1 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 182.2 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 132.1 24.00 0 55 0 0
#> 7.1 24.00 0 37 1 0
#> 67.1 24.00 0 25 0 0
#> 19.1 24.00 0 57 0 1
#> 198 24.00 0 66 0 1
#> 71.2 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 163 24.00 0 66 0 0
#> 120.1 24.00 0 68 0 1
#> 174.2 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 132.2 24.00 0 55 0 0
#> 82.2 24.00 0 34 0 0
#> 200.1 24.00 0 64 0 0
#> 142 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 7.2 24.00 0 37 1 0
#> 19.2 24.00 0 57 0 1
#> 21 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 160 24.00 0 31 1 0
#> 182.3 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.765 NA NA NA
#> 2 age, Cure model 0.0137 NA NA NA
#> 3 grade_ii, Cure model 0.0828 NA NA NA
#> 4 grade_iii, Cure model 0.899 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0216 NA NA NA
#> 2 grade_ii, Survival model 0.610 NA NA NA
#> 3 grade_iii, Survival model 0.453 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76518 0.01370 0.08282 0.89876
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 254.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76518109 0.01369916 0.08281942 0.89876461
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02156463 0.60990729 0.45334879
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9508679 0.9536177 0.9863251 0.7938623 0.9366792 0.7456713 0.5125149
#> [8] 0.9791902 0.7625674 0.6276826 0.8660401 0.9691740 0.2113506 0.7337283
#> [15] 0.9615099 0.9215580 0.4045026 0.9615099 0.7570527 0.6164406 0.7337283
#> [22] 0.9424399 0.8302051 0.8967977 0.3283860 0.9276374 0.9615099 0.6035134
#> [29] 0.8171073 0.7133051 0.8506862 0.5319978 0.7680428 0.9424399 0.8302051
#> [36] 0.8871552 0.6982990 0.9215580 0.9839689 0.2113506 0.9863251 0.9717098
#> [43] 0.9932662 0.9955465 0.7514781 0.6570415 0.9031815 0.8733603 0.6824958
#> [50] 0.9000033 0.8733603 0.8171073 0.6982990 0.7938623 0.5762137 0.9536177
#> [57] 0.5319978 0.8660401 0.8385604 0.7270844 0.6382738 0.8802855 0.7202546
#> [64] 0.9306764 0.8032665 0.7680428 0.9366792 0.9742206 0.8258984 0.4921966
#> [71] 0.9909711 0.7837660 0.9336973 0.9767157 0.7680428 0.8079178 0.6824958
#> [78] 0.9031815 0.9480789 0.8125354 0.3283860 0.8546259 0.9791902 0.9031815
#> [85] 0.9955465 0.6660914 0.8385604 0.9031815 0.8837370 0.9154483 0.7889501
#> [92] 0.8871552 0.8466882 0.8546259 0.6660914 0.9536177 0.9154483 0.4045026
#> [99] 0.4045026 0.6382738 0.4045026 0.5762137 0.8622593 0.5319978 0.8871552
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 43 107 149 41 37 76 113 183 8 36 26 52 24
#> 12.10 11.18 8.37 18.02 12.52 19.22 22.86 9.24 18.43 21.19 15.77 10.42 23.89
#> 55 159 155 69 159.1 179 197 55.1 42 23 157 78 14
#> 19.34 10.55 13.08 23.23 10.55 18.63 21.60 19.34 12.43 16.92 15.10 23.88 12.89
#> 159.2 136 111 158 181 63 88 42.1 23.1 167 128 155.1 16
#> 10.55 21.83 17.45 20.14 16.46 22.77 18.37 12.43 16.92 15.55 20.35 13.08 8.71
#> 24.1 149.1 93 25 127 97 32 96 125 68 133 125.1 111.1
#> 23.89 8.37 10.33 6.32 3.53 19.14 20.90 14.54 15.65 20.62 14.65 15.65 17.45
#> 128.1 41.1 15 107.1 63.1 26.1 171 170 90 6 166 154 40
#> 20.35 18.02 22.68 11.18 22.77 15.77 16.57 19.54 20.94 15.64 19.98 12.63 18.00
#> 88.1 37.1 61 30 92 77 108 177 187 88.2 184 68.1 96.1
#> 18.37 12.52 10.12 17.43 22.92 7.27 18.29 12.53 9.92 18.37 17.77 20.62 14.54
#> 49 117 78.1 188 183.1 96.2 127.1 190 171.1 96.3 39 81 51
#> 12.19 17.46 23.88 16.16 9.24 14.54 3.53 20.81 16.57 14.54 15.59 14.06 18.23
#> 167.1 130 188.1 190.1 107.2 81.1 69.1 69.2 90.1 69.3 15.1 100 63.2
#> 15.55 16.47 16.16 20.81 11.18 14.06 23.23 23.23 20.94 23.23 22.68 16.07 22.77
#> 167.2 87 71 182 174 173 137 35 65 71.1 147 83 174.1
#> 15.55 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 87.1 19 67 95 102 178 53 82 20 53.1 132 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 20.1 118 161 120 54 156 38 152 182.1 80 152.1 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 53.2 9 193 2 172 2.1 44 83.1 121 147.1 7 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 193.1 173.1 82.1 135 138 186 27 27.1 185 182.2 47 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 7.1 67.1 19.1 198 71.2 22 163 120.1 174.2 126 132.2 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 142 72.1 7.2 19.2 21 98 196 160 182.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002677435 0.114650151 -0.122104594
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.666656342 0.015312495 0.591804938
#> grade_iii, Cure model
#> -0.007923659
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 190 20.81 1 42 1 0
#> 199 19.81 1 NA 0 1
#> 190.1 20.81 1 42 1 0
#> 145 10.07 1 65 1 0
#> 170 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 180 14.82 1 37 0 0
#> 155 13.08 1 26 0 0
#> 175 21.91 1 43 0 0
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 58 19.34 1 39 0 0
#> 158 20.14 1 74 1 0
#> 199.1 19.81 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 158.1 20.14 1 74 1 0
#> 89 11.44 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 58.1 19.34 1 39 0 0
#> 45 17.42 1 54 0 1
#> 166 19.98 1 48 0 0
#> 85 16.44 1 36 0 0
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 168 23.72 1 70 0 0
#> 15 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 69 23.23 1 25 0 1
#> 180.1 14.82 1 37 0 0
#> 125.1 15.65 1 67 1 0
#> 55 19.34 1 69 0 1
#> 40 18.00 1 28 1 0
#> 10.2 10.53 1 34 0 0
#> 41 18.02 1 40 1 0
#> 55.1 19.34 1 69 0 1
#> 197 21.60 1 69 1 0
#> 90 20.94 1 50 0 1
#> 93 10.33 1 52 0 1
#> 171 16.57 1 41 0 1
#> 86 23.81 1 58 0 1
#> 124.1 9.73 1 NA 1 0
#> 190.2 20.81 1 42 1 0
#> 192 16.44 1 31 1 0
#> 175.1 21.91 1 43 0 0
#> 40.1 18.00 1 28 1 0
#> 70 7.38 1 30 1 0
#> 29 15.45 1 68 1 0
#> 190.3 20.81 1 42 1 0
#> 66 22.13 1 53 0 0
#> 39.1 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 55.2 19.34 1 69 0 1
#> 108.1 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 69.1 23.23 1 25 0 1
#> 15.1 22.68 1 48 0 0
#> 40.2 18.00 1 28 1 0
#> 187 9.92 1 39 1 0
#> 45.1 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 113 22.86 1 34 0 0
#> 45.2 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 100 16.07 1 60 0 0
#> 157.1 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 5 16.43 1 51 0 1
#> 194 22.40 1 38 0 1
#> 30 17.43 1 78 0 0
#> 76.1 19.22 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 124.2 9.73 1 NA 1 0
#> 10.3 10.53 1 34 0 0
#> 153.2 21.33 1 55 1 0
#> 51 18.23 1 83 0 1
#> 183.1 9.24 1 67 1 0
#> 36.1 21.19 1 48 0 1
#> 55.3 19.34 1 69 0 1
#> 45.3 17.42 1 54 0 1
#> 124.3 9.73 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 192.1 16.44 1 31 1 0
#> 130 16.47 1 53 0 1
#> 23 16.92 1 61 0 0
#> 145.2 10.07 1 65 1 0
#> 93.1 10.33 1 52 0 1
#> 63 22.77 1 31 1 0
#> 100.1 16.07 1 60 0 0
#> 149 8.37 1 33 1 0
#> 100.2 16.07 1 60 0 0
#> 167 15.55 1 56 1 0
#> 192.2 16.44 1 31 1 0
#> 130.1 16.47 1 53 0 1
#> 199.2 19.81 1 NA 0 1
#> 6 15.64 1 39 0 0
#> 128.1 20.35 1 35 0 1
#> 181 16.46 1 45 0 1
#> 187.1 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 58.2 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 89.1 11.44 1 NA 0 0
#> 83 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 191 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 31.1 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 120.1 24.00 0 68 0 1
#> 83.1 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 148.1 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 95 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 191.1 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 94 24.00 0 51 0 1
#> 121 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 17.1 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 84 24.00 0 39 0 1
#> 144.1 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 148.2 24.00 0 61 1 0
#> 144.2 24.00 0 28 0 1
#> 144.3 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 12 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 115.1 24.00 0 NA 1 0
#> 109 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 17.2 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 31.2 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 165.1 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 172.2 24.00 0 41 0 0
#> 17.3 24.00 0 38 0 1
#> 47 24.00 0 38 0 1
#> 116.1 24.00 0 58 0 1
#> 19 24.00 0 57 0 1
#> 82.1 24.00 0 34 0 0
#> 73.2 24.00 0 NA 0 1
#> 12.1 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 31.3 24.00 0 36 0 1
#> 31.4 24.00 0 36 0 1
#> 144.4 24.00 0 28 0 1
#> 94.2 24.00 0 51 0 1
#> 64.2 24.00 0 43 0 0
#> 9.1 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 152 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 198.1 24.00 0 66 0 1
#> 174 24.00 0 49 1 0
#> 82.2 24.00 0 34 0 0
#> 1.1 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.667 NA NA NA
#> 2 age, Cure model 0.0153 NA NA NA
#> 3 grade_ii, Cure model 0.592 NA NA NA
#> 4 grade_iii, Cure model -0.00792 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00268 NA NA NA
#> 2 grade_ii, Survival model 0.115 NA NA NA
#> 3 grade_iii, Survival model -0.122 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.666656 0.015312 0.591805 -0.007924
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.666656342 0.015312495 0.591804938 -0.007923659
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002677435 0.114650151 -0.122104594
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.933566593 0.174477526 0.174477526 0.878748690 0.264256796 0.641549022
#> [7] 0.599529558 0.737760602 0.781011096 0.095782754 0.122031268 0.802809891
#> [13] 0.273769822 0.236363914 0.802809891 0.878748690 0.236363914 0.759279903
#> [19] 0.273769822 0.455688559 0.254815579 0.547936457 0.435426039 0.356046751
#> [25] 0.007678919 0.062035962 0.770138829 0.673417721 0.030157736 0.737760602
#> [31] 0.641549022 0.273769822 0.395966586 0.802809891 0.385882354 0.273769822
#> [37] 0.113011865 0.165178294 0.856781938 0.506146528 0.002051949 0.174477526
#> [43] 0.547936457 0.095782754 0.395966586 0.966682209 0.705527151 0.174477526
#> [49] 0.086927703 0.673417721 0.336517163 0.273769822 0.356046751 0.845792477
#> [55] 0.022236949 0.716300379 0.014420606 0.030157736 0.062035962 0.395966586
#> [61] 0.911562659 0.455688559 0.988862784 0.208812247 0.045218166 0.455688559
#> [67] 0.147323988 0.610111563 0.716300379 0.977756878 0.588953062 0.078191053
#> [73] 0.445535585 0.336517163 0.122031268 0.802809891 0.122031268 0.375796138
#> [79] 0.933566593 0.147323988 0.273769822 0.455688559 0.218027557 0.547936457
#> [85] 0.516563616 0.495773630 0.878748690 0.856781938 0.053646850 0.610111563
#> [91] 0.955603109 0.610111563 0.694764640 0.547936457 0.516563616 0.662726124
#> [97] 0.218027557 0.537380654 0.911562659 0.791893553 0.273769822 0.425367783
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 183 190 190.1 145 170 125 79 180 155 175 153 10 58
#> 9.24 20.81 20.81 10.07 19.54 15.65 16.23 14.82 13.08 21.91 21.33 10.53 19.34
#> 158 10.1 145.1 158.1 133 58.1 45 166 85 111 108 168 15
#> 20.14 10.53 10.07 20.14 14.65 19.34 17.42 19.98 16.44 17.45 18.29 23.72 22.68
#> 81 39 69 180.1 125.1 55 40 10.2 41 55.1 197 90 93
#> 14.06 15.59 23.23 14.82 15.65 19.34 18.00 10.53 18.02 19.34 21.60 20.94 10.33
#> 171 86 190.2 192 175.1 40.1 70 29 190.3 66 39.1 76 55.2
#> 16.57 23.81 20.81 16.44 21.91 18.00 7.38 15.45 20.81 22.13 15.59 19.22 19.34
#> 108.1 52 129 157 164 69.1 15.1 40.2 187 45.1 127 68 113
#> 18.29 10.42 23.41 15.10 23.60 23.23 22.68 18.00 9.92 17.42 3.53 20.62 22.86
#> 45.2 36 100 157.1 91 5 194 30 76.1 153.1 10.3 153.2 51
#> 17.42 21.19 16.07 15.10 5.33 16.43 22.40 17.43 19.22 21.33 10.53 21.33 18.23
#> 183.1 36.1 55.3 45.3 128 192.1 130 23 145.2 93.1 63 100.1 149
#> 9.24 21.19 19.34 17.42 20.35 16.44 16.47 16.92 10.07 10.33 22.77 16.07 8.37
#> 100.2 167 192.2 130.1 6 128.1 181 187.1 159 58.2 184 83 31
#> 16.07 15.55 16.44 16.47 15.64 20.35 16.46 9.92 10.55 19.34 17.77 24.00 24.00
#> 103 17 1 112 120 191 9 148 31.1 44 120.1 83.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 148.1 82 95 28 191.1 53 94 121 172 143 165 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 17.1 71 44.1 84 144.1 148.2 144.2 144.3 173 12 172.1 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 151 193 109 98 131 17.2 103.1 31.2 141 163 193.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 112.1 46 138 118 64.1 172.2 17.3 47 116.1 19 82.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 31.3 31.4 144.4 94.2 64.2 9.1 198 11 152 87 198.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 1.1 132
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0102906 0.7958995 0.6904355
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.775991075 0.008595086 0.652666497
#> grade_iii, Cure model
#> 1.294647605
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 107 11.18 1 54 1 0
#> 111 17.45 1 47 0 1
#> 149 8.37 1 33 1 0
#> 154 12.63 1 20 1 0
#> 97 19.14 1 65 0 1
#> 106 16.67 1 49 1 0
#> 97.1 19.14 1 65 0 1
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 39 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 166 19.98 1 48 0 0
#> 171 16.57 1 41 0 1
#> 30 17.43 1 78 0 0
#> 63 22.77 1 31 1 0
#> 60 13.15 1 38 1 0
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 93 10.33 1 52 0 1
#> 101 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 180 14.82 1 37 0 0
#> 58 19.34 1 39 0 0
#> 169 22.41 1 46 0 0
#> 13 14.34 1 54 0 1
#> 149.1 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 86 23.81 1 58 0 1
#> 66 22.13 1 53 0 0
#> 26 15.77 1 49 0 1
#> 58.1 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 101.1 9.97 1 10 0 1
#> 117 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 133 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 164.1 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 69 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 134 17.81 1 47 1 0
#> 187 9.92 1 39 1 0
#> 90 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 13.1 14.34 1 54 0 1
#> 49 12.19 1 48 1 0
#> 41 18.02 1 40 1 0
#> 30.1 17.43 1 78 0 0
#> 24 23.89 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 108.1 18.29 1 39 0 1
#> 108.2 18.29 1 39 0 1
#> 168 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 39.1 15.59 1 37 0 1
#> 179.1 18.63 1 42 0 0
#> 150 20.33 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 79 16.23 1 54 1 0
#> 6.1 15.64 1 39 0 0
#> 169.1 22.41 1 46 0 0
#> 79.1 16.23 1 54 1 0
#> 16 8.71 1 71 0 1
#> 10 10.53 1 34 0 0
#> 110 17.56 1 65 0 1
#> 24.2 23.89 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 164.2 23.60 1 76 0 1
#> 15.1 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 106.1 16.67 1 49 1 0
#> 8 18.43 1 32 0 0
#> 114 13.68 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 88 18.37 1 47 0 0
#> 15.2 22.68 1 48 0 0
#> 37 12.52 1 57 1 0
#> 91 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 16.1 8.71 1 71 0 1
#> 52 10.42 1 52 0 1
#> 110.1 17.56 1 65 0 1
#> 123 13.00 1 44 1 0
#> 36 21.19 1 48 0 1
#> 26.1 15.77 1 49 0 1
#> 16.2 8.71 1 71 0 1
#> 88.1 18.37 1 47 0 0
#> 108.3 18.29 1 39 0 1
#> 16.3 8.71 1 71 0 1
#> 36.1 21.19 1 48 0 1
#> 129.1 23.41 1 53 1 0
#> 90.1 20.94 1 50 0 1
#> 45 17.42 1 54 0 1
#> 50.1 10.02 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 169.2 22.41 1 46 0 0
#> 101.2 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 36.2 21.19 1 48 0 1
#> 114.1 13.68 1 NA 0 0
#> 153.2 21.33 1 55 1 0
#> 21 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 95 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 12.1 24.00 0 63 0 0
#> 119 24.00 0 17 0 0
#> 143 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 119.1 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 71.1 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 109 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 163.1 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 67 24.00 0 25 0 0
#> 80 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 62.1 24.00 0 71 0 0
#> 12.2 24.00 0 63 0 0
#> 71.2 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 17 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 165.1 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 31.1 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 121 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 119.2 24.00 0 17 0 0
#> 122 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 27.1 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 119.3 24.00 0 17 0 0
#> 21.1 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 71.3 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 11.2 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 102.1 24.00 0 49 0 0
#> 71.4 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 73.1 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 22.2 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 2 24.00 0 9 0 0
#> 182 24.00 0 35 0 0
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 120 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.776 NA NA NA
#> 2 age, Cure model 0.00860 NA NA NA
#> 3 grade_ii, Cure model 0.653 NA NA NA
#> 4 grade_iii, Cure model 1.29 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0103 NA NA NA
#> 2 grade_ii, Survival model 0.796 NA NA NA
#> 3 grade_iii, Survival model 0.690 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.775991 0.008595 0.652666 1.294648
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.775991075 0.008595086 0.652666497 1.294647605
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0102906 0.7958995 0.6904355
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.02291401 0.08437572 0.80435726 0.84101904 0.54155407 0.97401312
#> [7] 0.79521037 0.37450071 0.58016081 0.37450071 0.22127404 0.83188249
#> [13] 0.70237769 0.61831263 0.31600967 0.59922599 0.55111557 0.12341429
#> [19] 0.77670119 0.89537778 0.85908689 0.88631765 0.90440348 0.68367957
#> [25] 0.13258895 0.05494356 0.73946568 0.33546797 0.16035854 0.75814829
#> [31] 0.97401312 0.11380362 0.03331715 0.20035282 0.65579321 0.33546797
#> [37] 0.19007750 0.90440348 0.53195365 0.44459519 0.74878113 0.36456925
#> [43] 0.60878840 0.05494356 0.21085463 0.73018724 0.10400345 0.29702748
#> [49] 0.50304145 0.93059072 0.27820153 0.39407820 0.75814829 0.82273944
#> [55] 0.48336586 0.55111557 0.00522381 0.44459519 0.44459519 0.04343882
#> [61] 0.33546797 0.61831263 0.70237769 0.39407820 0.30646128 0.00522381
#> [67] 0.72089689 0.63712773 0.68367957 0.16035854 0.63712773 0.93936281
#> [73] 0.86815040 0.51274526 0.00522381 0.84101904 0.05494356 0.13258895
#> [79] 0.58016081 0.41400318 0.67435064 0.42415793 0.13258895 0.81356044
#> [85] 0.99131560 0.32567187 0.93936281 0.87724192 0.51274526 0.78597808
#> [91] 0.25008728 0.65579321 0.93936281 0.42415793 0.44459519 0.93936281
#> [97] 0.25008728 0.08437572 0.27820153 0.57043954 0.22127404 0.16035854
#> [103] 0.90440348 0.49326855 0.25008728 0.22127404 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 78 129 177 107 111 149 154 97 106 97.1 153 43 39
#> 23.88 23.41 12.53 11.18 17.45 8.37 12.63 19.14 16.67 19.14 21.33 12.10 15.59
#> 85 166 171 30 63 60 61 159 93 101 6 15 164
#> 16.44 19.98 16.57 17.43 22.77 13.15 10.12 10.55 10.33 9.97 15.64 22.68 23.60
#> 180 58 169 13 149.1 92 86 66 26 58.1 194 101.1 117
#> 14.82 19.34 22.41 14.34 8.37 22.92 23.81 22.13 15.77 19.34 22.40 9.97 17.46
#> 108 133 76 181 164.1 139 29 69 190 134 187 90 179
#> 18.29 14.65 19.22 16.46 23.60 21.49 15.45 23.23 20.81 17.81 9.92 20.94 18.63
#> 13.1 49 41 30.1 24 108.1 108.2 168 55 192 39.1 179.1 150
#> 14.34 12.19 18.02 17.43 23.89 18.29 18.29 23.72 19.34 16.44 15.59 18.63 20.33
#> 24.1 167 79 6.1 169.1 79.1 16 10 110 24.2 107.1 164.2 15.1
#> 23.89 15.55 16.23 15.64 22.41 16.23 8.71 10.53 17.56 23.89 11.18 23.60 22.68
#> 106.1 8 125 88 15.2 37 91 105 16.1 52 110.1 123 36
#> 16.67 18.43 15.65 18.37 22.68 12.52 5.33 19.75 8.71 10.42 17.56 13.00 21.19
#> 26.1 16.2 88.1 108.3 16.3 36.1 129.1 90.1 45 153.1 169.2 101.2 40
#> 15.77 8.71 18.37 18.29 8.71 21.19 23.41 20.94 17.42 21.33 22.41 9.97 18.00
#> 36.2 153.2 21 12 151 163 28 95 84 98 62 12.1 119
#> 21.19 21.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 31 119.1 11 71 200 71.1 112 109 185 27 163.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 67 80 193 1 62.1 12.2 71.2 196 33 165 126 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 112.1 22 11.1 165.1 118 31.1 161 121 19 119.2 122 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 102 119.3 21.1 48 74 83 35 9 47 80.1 71.3 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 11.2 174 102.1 71.4 44 94 178 22.1 160 152 3 22.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 2 182 142 38 95.1 198 120 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0083317 0.4156030 0.2983315
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.1303984708 -0.0003928855 0.3795436948
#> grade_iii, Cure model
#> 0.7016100816
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 114 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 181 16.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 39 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 168 23.72 1 70 0 0
#> 93 10.33 1 52 0 1
#> 129 23.41 1 53 1 0
#> 10 10.53 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 14 12.89 1 21 0 0
#> 43.1 12.10 1 61 0 1
#> 133 14.65 1 57 0 0
#> 180 14.82 1 37 0 0
#> 15 22.68 1 48 0 0
#> 134 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 18 15.21 1 49 1 0
#> 55 19.34 1 69 0 1
#> 167 15.55 1 56 1 0
#> 14.1 12.89 1 21 0 0
#> 85 16.44 1 36 0 0
#> 117 17.46 1 26 0 1
#> 123 13.00 1 44 1 0
#> 92 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 76.1 19.22 1 54 0 1
#> 76.2 19.22 1 54 0 1
#> 42 12.43 1 49 0 1
#> 171 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 18.1 15.21 1 49 1 0
#> 58.1 19.34 1 39 0 0
#> 63 22.77 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 96.1 14.54 1 33 0 1
#> 111 17.45 1 47 0 1
#> 110 17.56 1 65 0 1
#> 171.1 16.57 1 41 0 1
#> 76.3 19.22 1 54 0 1
#> 108 18.29 1 39 0 1
#> 56 12.21 1 60 0 0
#> 181.1 16.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 18.2 15.21 1 49 1 0
#> 107 11.18 1 54 1 0
#> 125 15.65 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 85.1 16.44 1 36 0 0
#> 181.2 16.46 1 45 0 1
#> 134.1 17.81 1 47 1 0
#> 113 22.86 1 34 0 0
#> 181.3 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 101 9.97 1 10 0 1
#> 123.1 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 8 18.43 1 32 0 0
#> 124.2 9.73 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 188 16.16 1 46 0 1
#> 190.1 20.81 1 42 1 0
#> 167.1 15.55 1 56 1 0
#> 18.3 15.21 1 49 1 0
#> 57 14.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 159 10.55 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 88.1 18.37 1 47 0 0
#> 139 21.49 1 63 1 0
#> 61 10.12 1 36 0 1
#> 136.1 21.83 1 43 0 1
#> 167.2 15.55 1 56 1 0
#> 40 18.00 1 28 1 0
#> 145.2 10.07 1 65 1 0
#> 159.1 10.55 1 50 0 1
#> 18.4 15.21 1 49 1 0
#> 145.3 10.07 1 65 1 0
#> 8.1 18.43 1 32 0 0
#> 106 16.67 1 49 1 0
#> 117.2 17.46 1 26 0 1
#> 15.1 22.68 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 107.1 11.18 1 54 1 0
#> 177 12.53 1 75 0 0
#> 100 16.07 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 56.1 12.21 1 60 0 0
#> 76.4 19.22 1 54 0 1
#> 166 19.98 1 48 0 0
#> 96.2 14.54 1 33 0 1
#> 23 16.92 1 61 0 0
#> 76.5 19.22 1 54 0 1
#> 154.1 12.63 1 20 1 0
#> 57.1 14.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 100.1 16.07 1 60 0 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 151 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 12 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 95.1 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 19 24.00 0 57 0 1
#> 115 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 20 24.00 0 46 1 0
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 144.1 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 47 24.00 0 38 0 1
#> 47.1 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 47.2 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 146 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 152 24.00 0 36 0 1
#> 151.1 24.00 0 42 0 0
#> 104.1 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 104.2 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 185.2 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 34 24.00 0 36 0 0
#> 47.3 24.00 0 38 0 1
#> 34.1 24.00 0 36 0 0
#> 48.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 12.1 24.00 0 63 0 0
#> 95.2 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 12.2 24.00 0 63 0 0
#> 1 24.00 0 23 1 0
#> 116 24.00 0 58 0 1
#> 104.3 24.00 0 50 1 0
#> 9.1 24.00 0 31 1 0
#> 21.2 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 200.1 24.00 0 64 0 0
#> 144.2 24.00 0 28 0 1
#> 72.1 24.00 0 40 0 1
#> 12.3 24.00 0 63 0 0
#> 44 24.00 0 56 0 0
#> 44.1 24.00 0 56 0 0
#> 172.1 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 64 24.00 0 43 0 0
#> 44.2 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.130 NA NA NA
#> 2 age, Cure model -0.000393 NA NA NA
#> 3 grade_ii, Cure model 0.380 NA NA NA
#> 4 grade_iii, Cure model 0.702 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00833 NA NA NA
#> 2 grade_ii, Survival model 0.416 NA NA NA
#> 3 grade_iii, Survival model 0.298 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1303985 -0.0003929 0.3795437 0.7016101
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 259 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1303984708 -0.0003928855 0.3795436948 0.7016100816
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0083317 0.4156030 0.2983315
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.180335562 0.111470273 0.413610672 0.925391154 0.819335115 0.095867223
#> [7] 0.532395492 0.501727496 0.002131682 0.903950536 0.012790573 0.882668922
#> [13] 0.777471655 0.154010485 0.522126668 0.653663047 0.725714125 0.819335115
#> [19] 0.643247114 0.632894559 0.056713413 0.288512695 0.136395458 0.572983513
#> [25] 0.154010485 0.542666282 0.725714125 0.451841931 0.326878203 0.705063076
#> [31] 0.020636271 0.989262801 0.180335562 0.180335562 0.787907245 0.394168647
#> [37] 0.572983513 0.154010485 0.042630179 0.020636271 0.882668922 0.111470273
#> [43] 0.653663047 0.355205279 0.307566145 0.394168647 0.180335562 0.269034634
#> [49] 0.798357244 0.413610672 0.002131682 0.572983513 0.840415199 0.511913573
#> [55] 0.072067998 0.451841931 0.413610672 0.288512695 0.034406176 0.413610672
#> [61] 0.746459966 0.967762031 0.705063076 0.249861617 0.231154196 0.925391154
#> [67] 0.471601495 0.095867223 0.542666282 0.572983513 0.684381646 0.127776546
#> [73] 0.622586736 0.978504566 0.861513158 0.326878203 0.249861617 0.087627583
#> [79] 0.914670743 0.072067998 0.542666282 0.278807662 0.925391154 0.861513158
#> [85] 0.572983513 0.925391154 0.231154196 0.374767330 0.326878203 0.056713413
#> [91] 0.042630179 0.840415199 0.767044126 0.481604243 0.307566145 0.798357244
#> [97] 0.180335562 0.145114823 0.653663047 0.364934075 0.180335562 0.746459966
#> [103] 0.684381646 0.374767330 0.481604243 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 76 68 181 145 43 190 39 26 168 93 129 10 37
#> 19.22 20.62 16.46 10.07 12.10 20.81 15.59 15.77 23.72 10.33 23.41 10.53 12.52
#> 58 6 96 14 43.1 133 180 15 134 158 18 55 167
#> 19.34 15.64 14.54 12.89 12.10 14.65 14.82 22.68 17.81 20.14 15.21 19.34 15.55
#> 14.1 85 117 123 92 70 76.1 76.2 42 171 18.1 58.1 63
#> 12.89 16.44 17.46 13.00 22.92 7.38 19.22 19.22 12.43 16.57 15.21 19.34 22.77
#> 92.1 10.1 68.1 96.1 111 110 171.1 76.3 108 56 181.1 168.1 18.2
#> 22.92 10.53 20.62 14.54 17.45 17.56 16.57 19.22 18.29 12.21 16.46 23.72 15.21
#> 107 125 136 85.1 181.2 134.1 113 181.3 154 101 123.1 88 8
#> 11.18 15.65 21.83 16.44 16.46 17.81 22.86 16.46 12.63 9.97 13.00 18.37 18.43
#> 145.1 188 190.1 167.1 18.3 57 150 157 183 159 117.1 88.1 139
#> 10.07 16.16 20.81 15.55 15.21 14.46 20.33 15.10 9.24 10.55 17.46 18.37 21.49
#> 61 136.1 167.2 40 145.2 159.1 18.4 145.3 8.1 106 117.2 15.1 63.1
#> 10.12 21.83 15.55 18.00 10.07 10.55 15.21 10.07 18.43 16.67 17.46 22.68 22.77
#> 107.1 177 100 110.1 56.1 76.4 166 96.2 23 76.5 154.1 57.1 106.1
#> 11.18 12.53 16.07 17.56 12.21 19.22 19.98 14.54 16.92 19.22 12.63 14.46 16.67
#> 100.1 174 178 176 53 151 71 74 67 12 144 186 65
#> 16.07 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 176.1 95.1 141 200 19 11 20 82 104 156 21 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 144.1 161 47 47.1 35 47.2 54 146 163 160 185.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 3 21.1 71.1 102 152 151.1 104.1 9 172 104.2 142 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 185.2 22 198 34 47.3 34.1 48.1 162 7 12.1 95.2 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 12.2 1 116 104.3 9.1 21.2 131 174.1 28 33 142.1 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.2 72.1 12.3 44 44.1 172.1 19.1 64 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01593608 0.26045210 0.18610645
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.500131991 0.009433454 -0.055129747
#> grade_iii, Cure model
#> 0.927075559
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 49 12.19 1 48 1 0
#> 15 22.68 1 48 0 0
#> 180 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 195 11.76 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 124 9.73 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 123 13.00 1 44 1 0
#> 134 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 140 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 45 17.42 1 54 0 1
#> 93 10.33 1 52 0 1
#> 183 9.24 1 67 1 0
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 188 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 130 16.47 1 53 0 1
#> 197 21.60 1 69 1 0
#> 154.1 12.63 1 20 1 0
#> 14.1 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 57 14.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 133.1 14.65 1 57 0 0
#> 14.2 12.89 1 21 0 0
#> 101 9.97 1 10 0 1
#> 145 10.07 1 65 1 0
#> 169 22.41 1 46 0 0
#> 43.1 12.10 1 61 0 1
#> 187 9.92 1 39 1 0
#> 97 19.14 1 65 0 1
#> 88.1 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 49.1 12.19 1 48 1 0
#> 110 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 69 23.23 1 25 0 1
#> 189 10.51 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 184 17.77 1 38 0 0
#> 110.1 17.56 1 65 0 1
#> 36 21.19 1 48 0 1
#> 195.1 11.76 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 129.1 23.41 1 53 1 0
#> 169.1 22.41 1 46 0 0
#> 107 11.18 1 54 1 0
#> 123.1 13.00 1 44 1 0
#> 113.1 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 105 19.75 1 60 0 0
#> 181 16.46 1 45 0 1
#> 105.1 19.75 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 40 18.00 1 28 1 0
#> 183.1 9.24 1 67 1 0
#> 45.1 17.42 1 54 0 1
#> 129.2 23.41 1 53 1 0
#> 93.2 10.33 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 111 17.45 1 47 0 1
#> 164 23.60 1 76 0 1
#> 56 12.21 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 55 19.34 1 69 0 1
#> 107.1 11.18 1 54 1 0
#> 77.1 7.27 1 67 0 1
#> 187.1 9.92 1 39 1 0
#> 16 8.71 1 71 0 1
#> 140.1 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 101.1 9.97 1 10 0 1
#> 129.3 23.41 1 53 1 0
#> 59 10.16 1 NA 1 0
#> 105.2 19.75 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 101.2 9.97 1 10 0 1
#> 129.4 23.41 1 53 1 0
#> 36.1 21.19 1 48 0 1
#> 155 13.08 1 26 0 0
#> 99.2 21.19 1 38 0 1
#> 14.3 12.89 1 21 0 0
#> 86.1 23.81 1 58 0 1
#> 127 3.53 1 62 0 1
#> 81.1 14.06 1 34 0 0
#> 101.3 9.97 1 10 0 1
#> 154.2 12.63 1 20 1 0
#> 180.1 14.82 1 37 0 0
#> 25 6.32 1 34 1 0
#> 107.2 11.18 1 54 1 0
#> 197.1 21.60 1 69 1 0
#> 45.2 17.42 1 54 0 1
#> 5 16.43 1 51 0 1
#> 195.2 11.76 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 144 24.00 0 28 0 1
#> 119 24.00 0 17 0 0
#> 160 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 152.1 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 22.1 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 161 24.00 0 45 0 0
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 186.1 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 186.2 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 200.1 24.00 0 64 0 0
#> 104 24.00 0 50 1 0
#> 27.1 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 104.1 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 198 24.00 0 66 0 1
#> 34 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 72.1 24.00 0 40 0 1
#> 135 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 34.1 24.00 0 36 0 0
#> 200.2 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 152.2 24.00 0 36 0 1
#> 186.3 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 115 24.00 0 NA 1 0
#> 119.1 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 115.1 24.00 0 NA 1 0
#> 186.4 24.00 0 45 1 0
#> 11.1 24.00 0 42 0 1
#> 156 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 160.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 163 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 104.2 24.00 0 50 1 0
#> 119.2 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 182.1 24.00 0 35 0 0
#> 82.1 24.00 0 34 0 0
#> 71 24.00 0 51 0 0
#> 161.2 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 172 24.00 0 41 0 0
#> 148.1 24.00 0 61 1 0
#> 11.2 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.500 NA NA NA
#> 2 age, Cure model 0.00943 NA NA NA
#> 3 grade_ii, Cure model -0.0551 NA NA NA
#> 4 grade_iii, Cure model 0.927 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0159 NA NA NA
#> 2 grade_ii, Survival model 0.260 NA NA NA
#> 3 grade_iii, Survival model 0.186 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.500132 0.009433 -0.055130 0.927076
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 250.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.500131991 0.009433454 -0.055129747 0.927075559
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01593608 0.26045210 0.18610645
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2645093279 0.5736996734 0.0176352607 0.2953091564 0.4954319163
#> [6] 0.3166120423 0.5335114607 0.3970698018 0.1214892110 0.5467442073
#> [11] 0.6719341559 0.0527142233 0.1656826142 0.4698225685 0.3616167011
#> [16] 0.1738640784 0.7015815204 0.8532017903 0.9170717556 0.0952586349
#> [21] 0.4212690452 0.2355011467 0.0030597111 0.2078084240 0.0268277505
#> [26] 0.4954319163 0.4212690452 0.6010402331 0.0721079144 0.2746698643
#> [31] 0.3388064004 0.1015847554 0.3166120423 0.4212690452 0.7621862023
#> [36] 0.7466711967 0.0205488262 0.6010402331 0.8222508322 0.0890960903
#> [41] 0.1015847554 0.0126881237 0.5736996734 0.1426844760 0.1989298569
#> [46] 0.0103507185 0.0340736733 0.0001765023 0.1284525611 0.1426844760
#> [51] 0.0340736733 0.9663747821 0.6866819860 0.0030597111 0.0205488262
#> [56] 0.6290750675 0.3970698018 0.0126881237 0.2545605005 0.2355011467
#> [61] 0.0573258285 0.2168738554 0.0573258285 0.7015815204 0.0340736733
#> [66] 0.1146768314 0.8532017903 0.1738640784 0.0030597111 0.7015815204
#> [71] 0.2746698643 0.1577788583 0.0014300594 0.5601221166 0.1284525611
#> [76] 0.0721079144 0.6290750675 0.9170717556 0.8222508322 0.8847874976
#> [81] 0.4698225685 0.9009013401 0.7621862023 0.0030597111 0.0573258285
#> [86] 0.3388064004 0.7621862023 0.0030597111 0.0340736733 0.3850455053
#> [91] 0.0340736733 0.4212690452 0.0001765023 0.9831081020 0.3616167011
#> [96] 0.7621862023 0.4954319163 0.2953091564 0.9497977117 0.6290750675
#> [101] 0.0268277505 0.1738640784 0.2260981772 0.0831683314 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 125 49 15 180 154 133 177 123 134 42 159 166 30
#> 15.65 12.19 22.68 14.82 12.63 14.65 12.53 13.00 17.81 12.43 10.55 19.98 17.43
#> 140 81 45 93 183 77 8 14 188 129 130 197 154.1
#> 12.68 14.06 17.42 10.33 9.24 7.27 18.43 12.89 16.16 23.41 16.47 21.60 12.63
#> 14.1 43 58 6 57 88 133.1 14.2 101 145 169 43.1 187
#> 12.89 12.10 19.34 15.64 14.46 18.37 14.65 12.89 9.97 10.07 22.41 12.10 9.92
#> 97 88.1 113 49.1 110 171 69 99 86 184 110.1 36 91
#> 19.14 18.37 22.86 12.19 17.56 16.57 23.23 21.19 23.81 17.77 17.56 21.19 5.33
#> 52 129.1 169.1 107 123.1 113.1 100 188.1 105 181 105.1 93.1 99.1
#> 10.42 23.41 22.41 11.18 13.00 22.86 16.07 16.16 19.75 16.46 19.75 10.33 21.19
#> 40 183.1 45.1 129.2 93.2 6.1 111 164 56 184.1 55 107.1 77.1
#> 18.00 9.24 17.42 23.41 10.33 15.64 17.45 23.60 12.21 17.77 19.34 11.18 7.27
#> 187.1 16 140.1 70 101.1 129.3 105.2 57.1 101.2 129.4 36.1 155 99.2
#> 9.92 8.71 12.68 7.38 9.97 23.41 19.75 14.46 9.97 23.41 21.19 13.08 21.19
#> 14.3 86.1 127 81.1 101.3 154.2 180.1 25 107.2 197.1 45.2 5 76
#> 12.89 23.81 3.53 14.06 9.97 12.63 14.82 6.32 11.18 21.60 17.42 16.43 19.22
#> 144 119 160 116 3 186 151 103 152 38 165 83 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 152.1 27 22.1 174 161 11 146 72 186.1 35 109 186.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 200 200.1 104 27.1 2 104.1 82 198 34 44 165.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 72.1 135 176 12 34.1 200.2 102 182 152.2 186.3 131 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 162 161.1 75 143 193 20 119.1 65 186.4 11.1 156 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 135.1 163 80 104.2 119.2 20.1 87 62 28 182.1 82.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 21 148 172 148.1 11.2 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002632936 0.403948256 0.316171230
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.191107026 0.001414046 -0.131759074
#> grade_iii, Cure model
#> 1.124805197
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 140 12.68 1 59 1 0
#> 188 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 5 16.43 1 51 0 1
#> 110 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 169 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 169.1 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 184 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 55.1 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 194 22.40 1 38 0 1
#> 10 10.53 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 106 16.67 1 49 1 0
#> 60 13.15 1 38 1 0
#> 90 20.94 1 50 0 1
#> 90.1 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 188.1 16.16 1 46 0 1
#> 90.2 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 105 19.75 1 60 0 0
#> 63 22.77 1 31 1 0
#> 159.1 10.55 1 50 0 1
#> 61 10.12 1 36 0 1
#> 183 9.24 1 67 1 0
#> 60.1 13.15 1 38 1 0
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 164 23.60 1 76 0 1
#> 15 22.68 1 48 0 0
#> 187 9.92 1 39 1 0
#> 100 16.07 1 60 0 0
#> 99 21.19 1 38 0 1
#> 167 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 190 20.81 1 42 1 0
#> 169.2 22.41 1 46 0 0
#> 159.2 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 91 5.33 1 61 0 1
#> 124 9.73 1 NA 1 0
#> 159.3 10.55 1 50 0 1
#> 40 18.00 1 28 1 0
#> 111.1 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 42.1 12.43 1 49 0 1
#> 99.1 21.19 1 38 0 1
#> 111.2 17.45 1 47 0 1
#> 93.1 10.33 1 52 0 1
#> 113 22.86 1 34 0 0
#> 155 13.08 1 26 0 0
#> 108 18.29 1 39 0 1
#> 133 14.65 1 57 0 0
#> 52 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 111.3 17.45 1 47 0 1
#> 136 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 32 20.90 1 37 1 0
#> 129 23.41 1 53 1 0
#> 134 17.81 1 47 1 0
#> 154 12.63 1 20 1 0
#> 188.2 16.16 1 46 0 1
#> 184.1 17.77 1 38 0 0
#> 63.1 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 76 19.22 1 54 0 1
#> 6.1 15.64 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 4 17.64 1 NA 0 1
#> 175.1 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 133.2 14.65 1 57 0 0
#> 114 13.68 1 NA 0 0
#> 111.4 17.45 1 47 0 1
#> 128 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 153 21.33 1 55 1 0
#> 184.2 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 108.1 18.29 1 39 0 1
#> 18 15.21 1 49 1 0
#> 192 16.44 1 31 1 0
#> 179.1 18.63 1 42 0 0
#> 25 6.32 1 34 1 0
#> 60.2 13.15 1 38 1 0
#> 155.1 13.08 1 26 0 0
#> 32.1 20.90 1 37 1 0
#> 70 7.38 1 30 1 0
#> 180.1 14.82 1 37 0 0
#> 81 14.06 1 34 0 0
#> 114.1 13.68 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 164.1 23.60 1 76 0 1
#> 16.1 8.71 1 71 0 1
#> 133.3 14.65 1 57 0 0
#> 108.2 18.29 1 39 0 1
#> 119 24.00 0 17 0 0
#> 112 24.00 0 61 0 0
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 200 24.00 0 64 0 0
#> 135 24.00 0 58 1 0
#> 17 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 172 24.00 0 41 0 0
#> 17.1 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 146 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 116.1 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 115 24.00 0 NA 1 0
#> 21 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 143 24.00 0 51 0 0
#> 9.2 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 83 24.00 0 6 0 0
#> 112.1 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 19.1 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 44.1 24.00 0 56 0 0
#> 80 24.00 0 41 0 0
#> 65.2 24.00 0 57 1 0
#> 17.3 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 44.2 24.00 0 56 0 0
#> 174.2 24.00 0 49 1 0
#> 156.1 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 38.1 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 44.3 24.00 0 56 0 0
#> 38.2 24.00 0 31 1 0
#> 200.2 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 119.2 24.00 0 17 0 0
#> 19.2 24.00 0 57 0 1
#> 137.1 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 174.3 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 135.2 24.00 0 58 1 0
#> 126 24.00 0 48 0 0
#> 109 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 132.1 24.00 0 55 0 0
#> 21.1 24.00 0 47 0 0
#> 200.3 24.00 0 64 0 0
#> 75.1 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 162 24.00 0 51 0 0
#> 135.3 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.191 NA NA NA
#> 2 age, Cure model 0.00141 NA NA NA
#> 3 grade_ii, Cure model -0.132 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00263 NA NA NA
#> 2 grade_ii, Survival model 0.404 NA NA NA
#> 3 grade_iii, Survival model 0.316 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.191107 0.001414 -0.131759 1.124805
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 251.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.191107026 0.001414046 -0.131759074 1.124805197
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002632936 0.403948256 0.316171230
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78268170 0.56675852 0.48740631 0.85079323 0.54911899 0.46882291
#> [7] 0.82527380 0.32758933 0.13051407 0.61895867 0.13051407 0.80833771
#> [13] 0.44133997 0.35649788 0.32758933 0.31775221 0.16227848 0.88396298
#> [19] 0.54911899 0.53116316 0.73135250 0.23839957 0.23839957 0.67112314
#> [25] 0.56675852 0.23839957 0.84230874 0.17345559 0.40369883 0.30784610
#> [31] 0.09810705 0.85079323 0.91745157 0.95072807 0.73135250 0.60156515
#> [37] 0.79978778 0.03683451 0.11928389 0.94244558 0.59275179 0.21750365
#> [43] 0.65378608 0.62768584 0.64506572 0.02062706 0.28804410 0.13051407
#> [49] 0.85079323 0.47813999 0.99181943 0.85079323 0.42267181 0.48740631
#> [55] 0.90078463 0.80833771 0.21750365 0.48740631 0.90078463 0.08581821
#> [61] 0.75691669 0.37572847 0.68835380 0.89238159 0.93413743 0.07368090
#> [67] 0.48740631 0.19538557 0.41322321 0.26827424 0.06095366 0.43203849
#> [73] 0.79125419 0.56675852 0.44133997 0.09810705 0.60156515 0.92580436
#> [79] 0.34680492 0.62768584 0.68835380 0.17345559 0.00673104 0.68835380
#> [85] 0.48740631 0.29798638 0.77408263 0.20653210 0.44133997 0.83379859
#> [91] 0.37572847 0.66247256 0.54016945 0.35649788 0.98362749 0.73135250
#> [97] 0.75691669 0.26827424 0.97541027 0.67112314 0.72262018 0.95899216
#> [103] 0.03683451 0.95899216 0.68835380 0.37572847 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 140 188 111 159 5 110 56 55 169 125 169.1 42 184
#> 12.68 16.16 17.45 10.55 16.43 17.56 12.21 19.34 22.41 15.65 22.41 12.43 17.77
#> 179 55.1 170 194 10 5.1 106 60 90 90.1 180 188.1 90.2
#> 18.63 19.34 19.54 22.40 10.53 16.43 16.67 13.15 20.94 20.94 14.82 16.16 20.94
#> 107 175 51 105 63 159.1 61 183 60.1 26 177 164 15
#> 11.18 21.91 18.23 19.75 22.77 10.55 10.12 9.24 13.15 15.77 12.53 23.60 22.68
#> 187 100 99 167 6 39 168 190 169.2 159.2 117 91 159.3
#> 9.92 16.07 21.19 15.55 15.64 15.59 23.72 20.81 22.41 10.55 17.46 5.33 10.55
#> 40 111.1 93 42.1 99.1 111.2 93.1 113 155 108 133 52 101
#> 18.00 17.45 10.33 12.43 21.19 17.45 10.33 22.86 13.08 18.29 14.65 10.42 9.97
#> 69 111.3 136 41 32 129 134 154 188.2 184.1 63.1 26.1 145
#> 23.23 17.45 21.83 18.02 20.90 23.41 17.81 12.63 16.16 17.77 22.77 15.77 10.07
#> 76 6.1 133.1 175.1 78 133.2 111.4 128 123 153 184.2 43 108.1
#> 19.22 15.64 14.65 21.91 23.88 14.65 17.45 20.35 13.00 21.33 17.77 12.10 18.29
#> 18 192 179.1 25 60.2 155.1 32.1 70 180.1 81 16 164.1 16.1
#> 15.21 16.44 18.63 6.32 13.15 13.08 20.90 7.38 14.82 14.06 8.71 23.60 8.71
#> 133.3 108.2 119 112 160 74 185 48 174 200 135 17 174.1
#> 14.65 18.29 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 72 172 17.1 135.1 156 176 9 116 138 17.2 75 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 116.1 65 44 21 28 131 200.1 38 65.1 152 173 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 102 143 9.2 2 141 119.1 83 112.1 161 132 19.1 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 80 65.2 17.3 31 120 33 44.2 174.2 156.1 84 38.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 44.3 38.2 200.2 165 178 20 119.2 19.2 137.1 163 174.3 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.2 126 109 54 132.1 21.1 200.3 75.1 148 162 135.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0149314 0.2630450 -0.2127479
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.80665575 0.01215378 0.24733767
#> grade_iii, Cure model
#> 1.08771520
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 134 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 164 23.60 1 76 0 1
#> 105 19.75 1 60 0 0
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 154 12.63 1 20 1 0
#> 4 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 140 12.68 1 59 1 0
#> 154.1 12.63 1 20 1 0
#> 96 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 25 6.32 1 34 1 0
#> 184 17.77 1 38 0 0
#> 66 22.13 1 53 0 0
#> 180 14.82 1 37 0 0
#> 155.1 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 180.1 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 57 14.46 1 45 0 1
#> 117 17.46 1 26 0 1
#> 97 19.14 1 65 0 1
#> 99 21.19 1 38 0 1
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 15 22.68 1 48 0 0
#> 90 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 4.1 17.64 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 86 23.81 1 58 0 1
#> 159 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 66.1 22.13 1 53 0 0
#> 159.1 10.55 1 50 0 1
#> 51 18.23 1 83 0 1
#> 45 17.42 1 54 0 1
#> 97.1 19.14 1 65 0 1
#> 25.1 6.32 1 34 1 0
#> 50 10.02 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 129 23.41 1 53 1 0
#> 76.1 19.22 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 181.1 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 134.1 17.81 1 47 1 0
#> 55 19.34 1 69 0 1
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 5.1 16.43 1 51 0 1
#> 125.1 15.65 1 67 1 0
#> 32.1 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 14 12.89 1 21 0 0
#> 123 13.00 1 44 1 0
#> 100 16.07 1 60 0 0
#> 25.2 6.32 1 34 1 0
#> 86.1 23.81 1 58 0 1
#> 183 9.24 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 41 18.02 1 40 1 0
#> 49 12.19 1 48 1 0
#> 18 15.21 1 49 1 0
#> 69 23.23 1 25 0 1
#> 63 22.77 1 31 1 0
#> 177 12.53 1 75 0 0
#> 50.1 10.02 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 5.2 16.43 1 51 0 1
#> 76.2 19.22 1 54 0 1
#> 51.1 18.23 1 83 0 1
#> 60 13.15 1 38 1 0
#> 164.1 23.60 1 76 0 1
#> 155.2 13.08 1 26 0 0
#> 183.1 9.24 1 67 1 0
#> 133.1 14.65 1 57 0 0
#> 150.1 20.33 1 48 0 0
#> 29 15.45 1 68 1 0
#> 99.1 21.19 1 38 0 1
#> 159.2 10.55 1 50 0 1
#> 13 14.34 1 54 0 1
#> 128 20.35 1 35 0 1
#> 150.2 20.33 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 167 15.55 1 56 1 0
#> 90.1 20.94 1 50 0 1
#> 60.1 13.15 1 38 1 0
#> 58 19.34 1 39 0 0
#> 25.3 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 133.2 14.65 1 57 0 0
#> 30 17.43 1 78 0 0
#> 88 18.37 1 47 0 0
#> 183.2 9.24 1 67 1 0
#> 36 21.19 1 48 0 1
#> 164.2 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 102 24.00 0 49 0 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 178 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 75.1 24.00 0 21 1 0
#> 185.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 174.1 24.00 0 49 1 0
#> 121 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 112.1 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 31.1 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 1.1 24.00 0 23 1 0
#> 122 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 94.1 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 12.1 24.00 0 63 0 0
#> 19 24.00 0 57 0 1
#> 121.1 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 115.1 24.00 0 NA 1 0
#> 95.1 24.00 0 68 0 1
#> 174.2 24.00 0 49 1 0
#> 48.1 24.00 0 31 1 0
#> 12.2 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 87 24.00 0 27 0 0
#> 21.1 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 44.2 24.00 0 56 0 0
#> 34.1 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 102.2 24.00 0 49 0 0
#> 75.3 24.00 0 21 1 0
#> 116 24.00 0 58 0 1
#> 54 24.00 0 53 1 0
#> 147 24.00 0 76 1 0
#> 142 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 31.2 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 126.1 24.00 0 48 0 0
#> 103.1 24.00 0 56 1 0
#> 44.3 24.00 0 56 0 0
#> 31.3 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 121.2 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.807 NA NA NA
#> 2 age, Cure model 0.0122 NA NA NA
#> 3 grade_ii, Cure model 0.247 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0149 NA NA NA
#> 2 grade_ii, Survival model 0.263 NA NA NA
#> 3 grade_iii, Survival model -0.213 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80666 0.01215 0.24734 1.08772
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 246.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80665575 0.01215378 0.24733767 1.08771520
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0149314 0.2630450 -0.2127479
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.699667e-01 1.510399e-01 1.166189e-02 4.314257e-04 6.271953e-02
#> [6] 5.414280e-01 3.260643e-01 6.492717e-01 3.751902e-01 6.333022e-01
#> [11] 6.492717e-01 4.541078e-01 2.196539e-01 9.807451e-01 9.069200e-01
#> [16] 1.667648e-01 7.921344e-03 3.879691e-01 5.414280e-01 1.389943e-02
#> [21] 4.978719e-02 4.138172e-01 3.879691e-01 2.391005e-01 4.681732e-01
#> [26] 1.749941e-01 1.007207e-01 1.892634e-02 2.010239e-01 1.432577e-01
#> [31] 6.265602e-03 2.742449e-02 7.810016e-01 7.985213e-01 8.642709e-06
#> [36] 7.302004e-01 3.437378e-02 7.921344e-03 7.302004e-01 1.207644e-01
#> [41] 1.920838e-01 1.007207e-01 9.069200e-01 6.971167e-01 1.633001e-02
#> [46] 8.325761e-02 2.260573e-03 8.325761e-02 2.699667e-01 2.196539e-01
#> [51] 4.681732e-01 8.162382e-01 1.510399e-01 7.264831e-02 3.029782e-01
#> [56] 8.882139e-01 2.391005e-01 3.029782e-01 3.437378e-02 4.169926e-02
#> [61] 6.021236e-01 5.865473e-01 2.916654e-01 9.069200e-01 8.642709e-06
#> [66] 8.340727e-01 1.355359e-01 7.135886e-01 3.626270e-01 3.428529e-03
#> [71] 4.807919e-03 6.808719e-01 6.021236e-01 2.391005e-01 8.325761e-02
#> [76] 1.207644e-01 5.117235e-01 4.314257e-04 5.414280e-01 8.340727e-01
#> [81] 4.138172e-01 4.978719e-02 3.502247e-01 1.892634e-02 7.302004e-01
#> [86] 4.968790e-01 4.564996e-02 4.978719e-02 6.757915e-02 3.380503e-01
#> [91] 2.742449e-02 5.117235e-01 7.264831e-02 9.069200e-01 2.102081e-01
#> [96] 4.138172e-01 1.834021e-01 1.138113e-01 8.340727e-01 1.892634e-02
#> [101] 4.314257e-04 1.636572e-04 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 79 134 175 164 105 155 39 154 157 140 154.1 96 181
#> 16.23 17.81 21.91 23.60 19.75 13.08 15.59 12.63 15.10 12.68 12.63 14.54 16.46
#> 127 25 184 66 180 155.1 139 150 133 180.1 5 57 117
#> 3.53 6.32 17.77 22.13 14.82 13.08 21.49 20.33 14.65 14.82 16.43 14.46 17.46
#> 97 99 23 40 15 90 61 145 86 159 32 66.1 159.1
#> 19.14 21.19 16.92 18.00 22.68 20.94 10.12 10.07 23.81 10.55 20.90 22.13 10.55
#> 51 45 97.1 25.1 56 153 76 129 76.1 79.1 181.1 57.1 101
#> 18.23 17.42 19.14 6.32 12.21 21.33 19.22 23.41 19.22 16.23 16.46 14.46 9.97
#> 134.1 55 125 16 5.1 125.1 32.1 190 14 123 100 25.2 86.1
#> 17.81 19.34 15.65 8.71 16.43 15.65 20.90 20.81 12.89 13.00 16.07 6.32 23.81
#> 183 41 49 18 69 63 177 14.1 5.2 76.2 51.1 60 164.1
#> 9.24 18.02 12.19 15.21 23.23 22.77 12.53 12.89 16.43 19.22 18.23 13.15 23.60
#> 155.2 183.1 133.1 150.1 29 99.1 159.2 13 128 150.2 170 167 90.1
#> 13.08 9.24 14.65 20.33 15.45 21.19 10.55 14.34 20.35 20.33 19.54 15.55 20.94
#> 60.1 58 25.3 130 133.2 30 88 183.2 36 164.2 168 102 44
#> 13.15 19.34 6.32 16.47 14.65 17.43 18.37 9.24 21.19 23.60 23.72 24.00 24.00
#> 75 1 120 47 178 172 95 200 185 80 28 75.1 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 103 3 172.1 174.1 121 31 48 44.1 112 173 112.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 126 104 34 146 102.1 31.1 3.1 138 75.2 160 186 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 1.1 122 131 12 21 146.1 27 53 94 182 94.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 19 121.1 2 95.1 174.2 48.1 12.2 82 87 21.1 35 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.2 34.1 152 102.2 75.3 116 54 147 142 163 104.1 31.2 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 44.3 31.3 196 121.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008841176 0.883896962 0.228526759
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.60416603 0.03042767 0.26410974
#> grade_iii, Cure model
#> 0.78065288
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 189 10.51 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 37 12.52 1 57 1 0
#> 188 16.16 1 46 0 1
#> 133 14.65 1 57 0 0
#> 23 16.92 1 61 0 0
#> 117 17.46 1 26 0 1
#> 77 7.27 1 67 0 1
#> 37.1 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 70 7.38 1 30 1 0
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 66 22.13 1 53 0 0
#> 60.1 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 88 18.37 1 47 0 0
#> 86 23.81 1 58 0 1
#> 166 19.98 1 48 0 0
#> 99 21.19 1 38 0 1
#> 5 16.43 1 51 0 1
#> 194 22.40 1 38 0 1
#> 127 3.53 1 62 0 1
#> 106 16.67 1 49 1 0
#> 68 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 133.1 14.65 1 57 0 0
#> 187.1 9.92 1 39 1 0
#> 66.1 22.13 1 53 0 0
#> 136 21.83 1 43 0 1
#> 39 15.59 1 37 0 1
#> 5.1 16.43 1 51 0 1
#> 93 10.33 1 52 0 1
#> 175.1 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 60.2 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 86.1 23.81 1 58 0 1
#> 107 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 86.2 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 150 20.33 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 130 16.47 1 53 0 1
#> 24 23.89 1 38 0 0
#> 86.3 23.81 1 58 0 1
#> 153 21.33 1 55 1 0
#> 70.1 7.38 1 30 1 0
#> 23.1 16.92 1 61 0 0
#> 50 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 171.1 16.57 1 41 0 1
#> 42.1 12.43 1 49 0 1
#> 50.1 10.02 1 NA 1 0
#> 42.2 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 49 12.19 1 48 1 0
#> 181.2 16.46 1 45 0 1
#> 15 22.68 1 48 0 0
#> 140 12.68 1 59 1 0
#> 55 19.34 1 69 0 1
#> 158 20.14 1 74 1 0
#> 52 10.42 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 114 13.68 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 108 18.29 1 39 0 1
#> 136.1 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 129 23.41 1 53 1 0
#> 169.1 22.41 1 46 0 0
#> 129.1 23.41 1 53 1 0
#> 99.1 21.19 1 38 0 1
#> 105 19.75 1 60 0 0
#> 136.2 21.83 1 43 0 1
#> 66.2 22.13 1 53 0 0
#> 18 15.21 1 49 1 0
#> 79.1 16.23 1 54 1 0
#> 105.1 19.75 1 60 0 0
#> 26 15.77 1 49 0 1
#> 5.2 16.43 1 51 0 1
#> 99.2 21.19 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 97.1 19.14 1 65 0 1
#> 139 21.49 1 63 1 0
#> 77.1 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 166.1 19.98 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 181.3 16.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 107.1 11.18 1 54 1 0
#> 96 14.54 1 33 0 1
#> 105.2 19.75 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 51.1 18.23 1 83 0 1
#> 49.1 12.19 1 48 1 0
#> 169.2 22.41 1 46 0 0
#> 105.3 19.75 1 60 0 0
#> 174 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 72 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 132 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 132.1 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 19 24.00 0 57 0 1
#> 84 24.00 0 39 0 1
#> 176 24.00 0 43 0 1
#> 104 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 38 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 72.1 24.00 0 40 0 1
#> 132.2 24.00 0 55 0 0
#> 196 24.00 0 19 0 0
#> 31 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 80.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 121 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 121.1 24.00 0 57 1 0
#> 84.2 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 196.1 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 71.1 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 72.2 24.00 0 40 0 1
#> 11 24.00 0 42 0 1
#> 102 24.00 0 49 0 0
#> 84.3 24.00 0 39 0 1
#> 11.1 24.00 0 42 0 1
#> 137 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 84.4 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 98 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 73.1 24.00 0 NA 0 1
#> 73.2 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 185.1 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 84.5 24.00 0 39 0 1
#> 152 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 152.1 24.00 0 36 0 1
#> 34.2 24.00 0 36 0 0
#> 11.2 24.00 0 42 0 1
#> 80.2 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 132.3 24.00 0 55 0 0
#> 173 24.00 0 19 0 1
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 115.1 24.00 0 NA 1 0
#> 131.1 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 186 24.00 0 45 1 0
#> 138.1 24.00 0 44 1 0
#> 46.2 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.60 NA NA NA
#> 2 age, Cure model 0.0304 NA NA NA
#> 3 grade_ii, Cure model 0.264 NA NA NA
#> 4 grade_iii, Cure model 0.781 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00884 NA NA NA
#> 2 grade_ii, Survival model 0.884 NA NA NA
#> 3 grade_iii, Survival model 0.229 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.60417 0.03043 0.26411 0.78065
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.9
#> Residual Deviance: 246.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.60416603 0.03042767 0.26410974 0.78065288
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008841176 0.883896962 0.228526759
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.721084764 0.048601001 0.774108120 0.580292188 0.677164558 0.422925047
#> [7] 0.412509058 0.970048453 0.774108120 0.919904331 0.950256924 0.062607485
#> [13] 0.710022639 0.091816319 0.721084764 0.115625198 0.360527299 0.012350596
#> [19] 0.236934336 0.176144063 0.527395837 0.083929265 0.989963918 0.443926524
#> [25] 0.201236290 0.795020683 0.677164558 0.919904331 0.091816319 0.132879801
#> [31] 0.633850621 0.527395837 0.888939541 0.115625198 0.381213179 0.210098346
#> [37] 0.721084764 0.899358530 0.012350596 0.857931038 0.485849925 0.012350596
#> [43] 0.340362483 0.320541496 0.218989604 0.485849925 0.454411577 0.475259124
#> [49] 0.003047784 0.012350596 0.167482426 0.950256924 0.422925047 0.559252183
#> [55] 0.655474177 0.454411577 0.795020683 0.795020683 0.752718929 0.837064964
#> [61] 0.485849925 0.055450994 0.763446226 0.291662087 0.228007515 0.878545702
#> [67] 0.291662087 0.940127464 0.370854398 0.132879801 0.826410197 0.036145433
#> [73] 0.062607485 0.036145433 0.176144063 0.254911696 0.132879801 0.091816319
#> [79] 0.644714012 0.559252183 0.254911696 0.612213546 0.527395837 0.176144063
#> [85] 0.320541496 0.340362483 0.158596550 0.970048453 0.601457502 0.580292188
#> [91] 0.402093436 0.666294740 0.236934336 0.291662087 0.485849925 0.623004687
#> [97] 0.857931038 0.699005082 0.254911696 0.899358530 0.381213179 0.837064964
#> [103] 0.062607485 0.254911696 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 60 92 37 188 133 23 117 77 37.1 187 70 169 81
#> 13.15 22.92 12.52 16.16 14.65 16.92 17.46 7.27 12.52 9.92 7.38 22.41 14.06
#> 66 60.1 175 88 86 166 99 5 194 127 106 68 42
#> 22.13 13.15 21.91 18.37 23.81 19.98 21.19 16.43 22.40 3.53 16.67 20.62 12.43
#> 133.1 187.1 66.1 136 39 5.1 93 175.1 51 128 60.2 145 86.1
#> 14.65 9.92 22.13 21.83 15.59 16.43 10.33 21.91 18.23 20.35 13.15 10.07 23.81
#> 107 181 86.2 97 76 150 181.1 171 130 24 86.3 153 70.1
#> 11.18 16.46 23.81 19.14 19.22 20.33 16.46 16.57 16.47 23.89 23.81 21.33 7.38
#> 23.1 79 157 171.1 42.1 42.2 155 49 181.2 15 140 55 158
#> 16.92 16.23 15.10 16.57 12.43 12.43 13.08 12.19 16.46 22.68 12.68 19.34 20.14
#> 52 58 183 108 136.1 56 129 169.1 129.1 99.1 105 136.2 66.2
#> 10.42 19.34 9.24 18.29 21.83 12.21 23.41 22.41 23.41 21.19 19.75 21.83 22.13
#> 18 79.1 105.1 26 5.2 99.2 76.1 97.1 139 77.1 100 188.1 134
#> 15.21 16.23 19.75 15.77 16.43 21.19 19.22 19.14 21.49 7.27 16.07 16.16 17.81
#> 180 166.1 55.1 181.3 6 107.1 96 105.2 145.1 51.1 49.1 169.2 105.3
#> 14.82 19.98 19.34 16.46 15.64 11.18 14.54 19.75 10.07 18.23 12.19 22.41 19.75
#> 174 21 146 193 33 116 72 87 132 46 132.1 160 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 84 176 104 80 185 146.1 148 38 138 116.1 72.1 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 31 165 80.1 17 84.1 121 46.1 121.1 84.2 71 27 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 71.1 28 72.2 11 102 84.3 11.1 137 3 182 84.4 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 191 53 185.1 109 34.1 131 84.5 152 35 148.1 152.1 34.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.2 80.2 35.1 2 9 95 112 132.3 173 62 33.1 131.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 126 186 138.1 46.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001959867 0.465356013 0.367210693
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.003438990 0.005768797 -0.226448128
#> grade_iii, Cure model
#> 0.186868038
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 96 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 123 13.00 1 44 1 0
#> 136 21.83 1 43 0 1
#> 192 16.44 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 70.1 7.38 1 30 1 0
#> 90 20.94 1 50 0 1
#> 194 22.40 1 38 0 1
#> 171 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 180 14.82 1 37 0 0
#> 13 14.34 1 54 0 1
#> 56 12.21 1 60 0 0
#> 14 12.89 1 21 0 0
#> 190 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 170 19.54 1 43 0 1
#> 42 12.43 1 49 0 1
#> 91 5.33 1 61 0 1
#> 14.1 12.89 1 21 0 0
#> 63 22.77 1 31 1 0
#> 157 15.10 1 47 0 0
#> 24.1 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 24.2 23.89 1 38 0 0
#> 36 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 188 16.16 1 46 0 1
#> 99 21.19 1 38 0 1
#> 40 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 16 8.71 1 71 0 1
#> 25.1 6.32 1 34 1 0
#> 10 10.53 1 34 0 0
#> 6 15.64 1 39 0 0
#> 70.2 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 133 14.65 1 57 0 0
#> 37 12.52 1 57 1 0
#> 125.1 15.65 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 123.1 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 76 19.22 1 54 0 1
#> 180.1 14.82 1 37 0 0
#> 88 18.37 1 47 0 0
#> 105 19.75 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 18.1 15.21 1 49 1 0
#> 63.1 22.77 1 31 1 0
#> 125.2 15.65 1 67 1 0
#> 91.1 5.33 1 61 0 1
#> 70.3 7.38 1 30 1 0
#> 37.1 12.52 1 57 1 0
#> 183 9.24 1 67 1 0
#> 14.2 12.89 1 21 0 0
#> 45 17.42 1 54 0 1
#> 41 18.02 1 40 1 0
#> 167 15.55 1 56 1 0
#> 43 12.10 1 61 0 1
#> 88.1 18.37 1 47 0 0
#> 90.1 20.94 1 50 0 1
#> 170.2 19.54 1 43 0 1
#> 14.3 12.89 1 21 0 0
#> 45.1 17.42 1 54 0 1
#> 56.1 12.21 1 60 0 0
#> 6.1 15.64 1 39 0 0
#> 149 8.37 1 33 1 0
#> 45.2 17.42 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 155 13.08 1 26 0 0
#> 190.1 20.81 1 42 1 0
#> 69 23.23 1 25 0 1
#> 96.1 14.54 1 33 0 1
#> 153 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 166 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 45.3 17.42 1 54 0 1
#> 24.3 23.89 1 38 0 0
#> 134 17.81 1 47 1 0
#> 50.1 10.02 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 29 15.45 1 68 1 0
#> 130 16.47 1 53 0 1
#> 179 18.63 1 42 0 0
#> 117 17.46 1 26 0 1
#> 180.2 14.82 1 37 0 0
#> 169 22.41 1 46 0 0
#> 127 3.53 1 62 0 1
#> 42.1 12.43 1 49 0 1
#> 179.1 18.63 1 42 0 0
#> 52 10.42 1 52 0 1
#> 155.1 13.08 1 26 0 0
#> 187 9.92 1 39 1 0
#> 93 10.33 1 52 0 1
#> 30 17.43 1 78 0 0
#> 134.1 17.81 1 47 1 0
#> 24.4 23.89 1 38 0 0
#> 6.2 15.64 1 39 0 0
#> 40.1 18.00 1 28 1 0
#> 146 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 186 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 165 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 191 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 74 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 193.1 24.00 0 45 0 1
#> 94.1 24.00 0 51 0 1
#> 198.1 24.00 0 66 0 1
#> 3.1 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 65.1 24.00 0 57 1 0
#> 20.1 24.00 0 46 1 0
#> 196 24.00 0 19 0 0
#> 64.1 24.00 0 43 0 0
#> 11 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 152.1 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 48.1 24.00 0 31 1 0
#> 104.1 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 143 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 178 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 196.1 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 65.2 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 119 24.00 0 17 0 0
#> 126.1 24.00 0 48 0 0
#> 48.2 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 64.2 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 198.2 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 27.1 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 20.2 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 98.1 24.00 0 34 1 0
#> 120 24.00 0 68 0 1
#> 198.3 24.00 0 66 0 1
#> 120.1 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 2.1 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 126.2 24.00 0 48 0 0
#> 38.1 24.00 0 31 1 0
#> 94.2 24.00 0 51 0 1
#> 21.1 24.00 0 47 0 0
#> 151.1 24.00 0 42 0 0
#> 11.1 24.00 0 42 0 1
#> 104.2 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.00344 NA NA NA
#> 2 age, Cure model 0.00577 NA NA NA
#> 3 grade_ii, Cure model -0.226 NA NA NA
#> 4 grade_iii, Cure model 0.187 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00196 NA NA NA
#> 2 grade_ii, Survival model 0.465 NA NA NA
#> 3 grade_iii, Survival model 0.367 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.003439 0.005769 -0.226448 0.186868
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 263.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.003438990 0.005768797 -0.226448128 0.186868038
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001959867 0.465356013 0.367210693
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.04865824 0.72845224 0.94301637 0.76471991 0.24560545 0.57570402
#> [7] 0.61601581 0.94301637 0.30500302 0.23205311 0.55907732 0.96844951
#> [13] 0.86942179 0.69908550 0.74300204 0.84885582 0.77897197 0.32687781
#> [19] 0.59202638 0.37861840 0.83511293 0.98113294 0.77897197 0.19077498
#> [25] 0.69166467 0.04865824 0.34773562 0.04865824 0.27138673 0.14346713
#> [31] 0.60006855 0.27138673 0.46426047 0.90995020 0.92989119 0.96844951
#> [37] 0.88300948 0.63889446 0.94301637 0.60804870 0.37861840 0.72106051
#> [43] 0.82123549 0.61601581 0.88300948 0.67688741 0.76471991 0.12310675
#> [49] 0.87623124 0.40728143 0.69908550 0.43592616 0.36835774 0.27138673
#> [55] 0.67688741 0.19077498 0.61601581 0.98113294 0.94301637 0.82123549
#> [61] 0.92328171 0.77897197 0.51767465 0.45484404 0.66170831 0.86257100
#> [67] 0.43592616 0.30500302 0.37861840 0.77897197 0.51767465 0.84885582
#> [73] 0.63889446 0.93646985 0.51767465 0.14346713 0.75026964 0.32687781
#> [79] 0.17499651 0.72845224 0.25874437 0.55065633 0.35806131 0.58389916
#> [85] 0.80717250 0.51767465 0.04865824 0.48240529 0.80717250 0.66933312
#> [91] 0.56742731 0.41692888 0.50005485 0.69908550 0.21804688 0.99371439
#> [97] 0.83511293 0.41692888 0.89649973 0.75026964 0.91663338 0.90323995
#> [103] 0.50887734 0.48240529 0.04865824 0.63889446 0.46426047 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 24 96 70 123 136 192 125 70.1 90 194 171 25 107
#> 23.89 14.54 7.38 13.00 21.83 16.44 15.65 7.38 20.94 22.40 16.57 6.32 11.18
#> 180 13 56 14 190 79 170 42 91 14.1 63 157 24.1
#> 14.82 14.34 12.21 12.89 20.81 16.23 19.54 12.43 5.33 12.89 22.77 15.10 23.89
#> 158 24.2 36 129 188 99 40 61 16 25.1 10 6 70.2
#> 20.14 23.89 21.19 23.41 16.16 21.19 18.00 10.12 8.71 6.32 10.53 15.64 7.38
#> 100 170.1 133 37 125.1 10.1 18 123.1 168 159 76 180.1 88
#> 16.07 19.54 14.65 12.52 15.65 10.53 15.21 13.00 23.72 10.55 19.22 14.82 18.37
#> 105 36.1 18.1 63.1 125.2 91.1 70.3 37.1 183 14.2 45 41 167
#> 19.75 21.19 15.21 22.77 15.65 5.33 7.38 12.52 9.24 12.89 17.42 18.02 15.55
#> 43 88.1 90.1 170.2 14.3 45.1 56.1 6.1 149 45.2 129.1 155 190.1
#> 12.10 18.37 20.94 19.54 12.89 17.42 12.21 15.64 8.37 17.42 23.41 13.08 20.81
#> 69 96.1 153 23 166 5 154 45.3 24.3 134 154.1 29 130
#> 23.23 14.54 21.33 16.92 19.98 16.43 12.63 17.42 23.89 17.81 12.63 15.45 16.47
#> 179 117 180.2 169 127 42.1 179.1 52 155.1 187 93 30 134.1
#> 18.63 17.46 14.82 22.41 3.53 12.43 18.63 10.42 13.08 9.92 10.33 17.43 17.81
#> 24.4 6.2 40.1 146 7 38 48 193 3 104 65 27 116
#> 23.89 15.64 18.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 198 165 138 64 20 191 83 152 74 94 80 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 94.1 198.1 3.1 98 65.1 20.1 196 64.1 11 121 33 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 48.1 104.1 47 83.1 143 151 178 141 118 74.1 196.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 67 65.2 173 119 126.1 48.2 21 75 64.2 185 186.1 198.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 46.1 27.1 35 143.1 174.1 20.2 182 1 2 98.1 120 198.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 185.1 2.1 156 126.2 38.1 94.2 21.1 151.1 11.1 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004162171 0.614531671 0.544642999
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.716375391 0.006295722 0.571445664
#> grade_iii, Cure model
#> 1.482987442
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 181 16.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 117 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 5 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 32 20.90 1 37 1 0
#> 129 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 32.1 20.90 1 37 1 0
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 155 13.08 1 26 0 0
#> 169 22.41 1 46 0 0
#> 88 18.37 1 47 0 0
#> 171.1 16.57 1 41 0 1
#> 188 16.16 1 46 0 1
#> 60 13.15 1 38 1 0
#> 52 10.42 1 52 0 1
#> 5.1 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 150 20.33 1 48 0 0
#> 145 10.07 1 65 1 0
#> 10.1 10.53 1 34 0 0
#> 149 8.37 1 33 1 0
#> 18.1 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 91 5.33 1 61 0 1
#> 88.1 18.37 1 47 0 0
#> 56 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 78 23.88 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 181.1 16.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 63 22.77 1 31 1 0
#> 140 12.68 1 59 1 0
#> 50 10.02 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 63.1 22.77 1 31 1 0
#> 79 16.23 1 54 1 0
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 125 15.65 1 67 1 0
#> 155.1 13.08 1 26 0 0
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 4.1 17.64 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 175 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 55 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 130 16.47 1 53 0 1
#> 55.1 19.34 1 69 0 1
#> 171.2 16.57 1 41 0 1
#> 170 19.54 1 43 0 1
#> 50.1 10.02 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 49 12.19 1 48 1 0
#> 41 18.02 1 40 1 0
#> 110 17.56 1 65 0 1
#> 184.1 17.77 1 38 0 0
#> 133.1 14.65 1 57 0 0
#> 170.1 19.54 1 43 0 1
#> 125.1 15.65 1 67 1 0
#> 18.2 15.21 1 49 1 0
#> 70 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 167 15.55 1 56 1 0
#> 150.1 20.33 1 48 0 0
#> 171.3 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 25.1 6.32 1 34 1 0
#> 145.1 10.07 1 65 1 0
#> 66 22.13 1 53 0 0
#> 68.1 20.62 1 44 0 0
#> 167.1 15.55 1 56 1 0
#> 23 16.92 1 61 0 0
#> 18.3 15.21 1 49 1 0
#> 39 15.59 1 37 0 1
#> 57.1 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 171.4 16.57 1 41 0 1
#> 50.2 10.02 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 125.2 15.65 1 67 1 0
#> 25.2 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 10.2 10.53 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 69 23.23 1 25 0 1
#> 16.1 8.71 1 71 0 1
#> 66.1 22.13 1 53 0 0
#> 175.1 21.91 1 43 0 0
#> 23.1 16.92 1 61 0 0
#> 99.1 21.19 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 25.3 6.32 1 34 1 0
#> 169.1 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 109 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 115 24.00 0 NA 1 0
#> 147.1 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 33 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 193 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 122 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 35.1 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 147.2 24.00 0 76 1 0
#> 2 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 148.2 24.00 0 61 1 0
#> 82.1 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 22 24.00 0 52 1 0
#> 102.1 24.00 0 49 0 0
#> 163.1 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 82.2 24.00 0 34 0 0
#> 2.1 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 104 24.00 0 50 1 0
#> 82.3 24.00 0 34 0 0
#> 62.1 24.00 0 71 0 0
#> 54.1 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 144.1 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 103.1 24.00 0 56 1 0
#> 182.1 24.00 0 35 0 0
#> 54.2 24.00 0 53 1 0
#> 115.1 24.00 0 NA 1 0
#> 119 24.00 0 17 0 0
#> 144.2 24.00 0 28 0 1
#> 7.1 24.00 0 37 1 0
#> 65.1 24.00 0 57 1 0
#> 62.2 24.00 0 71 0 0
#> 62.3 24.00 0 71 0 0
#> 144.3 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 144.4 24.00 0 28 0 1
#> 62.4 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 162 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 82.4 24.00 0 34 0 0
#> 200.1 24.00 0 64 0 0
#> 137.1 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 98 24.00 0 34 1 0
#> 121.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 163.2 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.716 NA NA NA
#> 2 age, Cure model 0.00630 NA NA NA
#> 3 grade_ii, Cure model 0.571 NA NA NA
#> 4 grade_iii, Cure model 1.48 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00416 NA NA NA
#> 2 grade_ii, Survival model 0.615 NA NA NA
#> 3 grade_iii, Survival model 0.545 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.716375 0.006296 0.571446 1.482987
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 244.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.716375391 0.006295722 0.571445664 1.482987442
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004162171 0.614531671 0.544642999
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.582020011 0.528431761 0.480939414 0.726790060 0.599890362 0.847480035
#> [7] 0.451733605 0.422075391 0.694450453 0.269055541 0.061954693 0.188004250
#> [13] 0.269055541 0.963277413 0.767631380 0.115245462 0.391907024 0.528431761
#> [19] 0.626388200 0.759499298 0.870972288 0.599890362 0.955719710 0.320578367
#> [25] 0.902201292 0.847480035 0.940529390 0.694450453 0.289514896 0.992604266
#> [31] 0.391907024 0.823765814 0.800014528 0.007005707 0.582020011 0.925287123
#> [37] 0.092565549 0.791947905 0.023166656 0.092565549 0.617553312 0.490592999
#> [43] 0.490592999 0.643727678 0.767631380 0.412012615 0.743221958 0.236376702
#> [49] 0.886595430 0.163066422 0.894414838 0.371983225 0.310219615 0.572893905
#> [55] 0.371983225 0.528431761 0.351741421 0.800014528 0.831704728 0.432085579
#> [61] 0.471178637 0.451733605 0.726790060 0.351741421 0.643727678 0.694450453
#> [67] 0.948143768 0.341198944 0.677686984 0.320578367 0.528431761 0.783844452
#> [73] 0.963277413 0.902201292 0.138744088 0.289514896 0.677686984 0.509433577
#> [79] 0.694450453 0.669154140 0.743221958 0.441966392 0.528431761 0.200537044
#> [85] 0.643727678 0.963277413 0.212774003 0.847480035 0.870972288 0.917598365
#> [91] 0.815843773 0.224721027 0.839604883 0.078080609 0.925287123 0.138744088
#> [97] 0.163066422 0.509433577 0.236376702 0.626388200 0.043565869 0.963277413
#> [103] 0.115245462 0.258128486 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 181 171 117 133 5 10 184 51 18 32 129 136 32.1
#> 16.46 16.57 17.46 14.65 16.43 10.53 17.77 18.23 15.21 20.90 23.41 21.83 20.90
#> 25 155 169 88 171.1 188 60 52 5.1 77 150 145 10.1
#> 6.32 13.08 22.41 18.37 16.57 16.16 13.15 10.42 16.43 7.27 20.33 10.07 10.53
#> 149 18.1 68 91 88.1 56 154 78 181.1 16 63 140 168
#> 8.37 15.21 20.62 5.33 18.37 12.21 12.63 23.88 16.46 8.71 22.77 12.68 23.72
#> 63.1 79 45 45.1 125 155.1 108 57 99 93 175 61 55
#> 22.77 16.23 17.42 17.42 15.65 13.08 18.29 14.46 21.19 10.33 21.91 10.12 19.34
#> 128 130 55.1 171.2 170 154.1 49 41 110 184.1 133.1 170.1 125.1
#> 20.35 16.47 19.34 16.57 19.54 12.63 12.19 18.02 17.56 17.77 14.65 19.54 15.65
#> 18.2 70 105 167 150.1 171.3 123 25.1 145.1 66 68.1 167.1 23
#> 15.21 7.38 19.75 15.55 20.33 16.57 13.00 6.32 10.07 22.13 20.62 15.55 16.92
#> 18.3 39 57.1 134 171.4 197 125.2 25.2 139 10.2 52.1 101 42
#> 15.21 15.59 14.46 17.81 16.57 21.60 15.65 6.32 21.49 10.53 10.42 9.97 12.43
#> 153 43 69 16.1 66.1 175.1 23.1 99.1 188.1 164 25.3 169.1 90
#> 21.33 12.10 23.23 8.71 22.13 21.91 16.92 21.19 16.16 23.60 6.32 22.41 20.94
#> 109 143 62 44 11 163 147 147.1 17 3 35 174 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 200 148 148.1 34 152 54 126 102 94 137 112 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 122 109.1 35.1 144 82 147.2 2 7 148.2 82.1 132 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 163.1 196.1 82.2 2.1 142 80 103 104 82.3 62.1 54.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 182 121 65 116 103.1 182.1 54.2 119 144.2 7.1 65.1 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.3 144.3 131 144.4 62.4 138 84 162 84.1 82.4 200.1 137.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 98 121.1 53 38 152.1 163.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0063968946 0.0002778921 0.0297224152
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.14921877 0.02317052 -0.21904521
#> grade_iii, Cure model
#> 0.67558324
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 133 14.65 1 57 0 0
#> 189 10.51 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 111 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 4.1 17.64 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 90 20.94 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 77.1 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 180 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 136.1 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 13.1 14.34 1 54 0 1
#> 155 13.08 1 26 0 0
#> 127 3.53 1 62 0 1
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 90.1 20.94 1 50 0 1
#> 45 17.42 1 54 0 1
#> 29 15.45 1 68 1 0
#> 29.1 15.45 1 68 1 0
#> 91 5.33 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 111.1 17.45 1 47 0 1
#> 164.1 23.60 1 76 0 1
#> 157 15.10 1 47 0 0
#> 30 17.43 1 78 0 0
#> 155.1 13.08 1 26 0 0
#> 59.1 10.16 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 197.1 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 125.2 15.65 1 67 1 0
#> 166.1 19.98 1 48 0 0
#> 150 20.33 1 48 0 0
#> 153 21.33 1 55 1 0
#> 153.1 21.33 1 55 1 0
#> 130 16.47 1 53 0 1
#> 89.2 11.44 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 136.2 21.83 1 43 0 1
#> 199.1 19.81 1 NA 0 1
#> 63.1 22.77 1 31 1 0
#> 197.2 21.60 1 69 1 0
#> 157.1 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 55 19.34 1 69 0 1
#> 179 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 61.1 10.12 1 36 0 1
#> 100.1 16.07 1 60 0 0
#> 61.2 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 90.2 20.94 1 50 0 1
#> 130.1 16.47 1 53 0 1
#> 13.2 14.34 1 54 0 1
#> 157.2 15.10 1 47 0 0
#> 29.2 15.45 1 68 1 0
#> 29.3 15.45 1 68 1 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 184 17.77 1 38 0 0
#> 15.1 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 89.3 11.44 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 124.1 9.73 1 NA 1 0
#> 199.2 19.81 1 NA 0 1
#> 85.1 16.44 1 36 0 0
#> 166.2 19.98 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 77.2 7.27 1 67 0 1
#> 175 21.91 1 43 0 0
#> 133.2 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 170 19.54 1 43 0 1
#> 42 12.43 1 49 0 1
#> 10 10.53 1 34 0 0
#> 14 12.89 1 21 0 0
#> 168 23.72 1 70 0 0
#> 58 19.34 1 39 0 0
#> 146 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 186 24.00 0 45 1 0
#> 1.1 24.00 0 23 1 0
#> 173 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 44 24.00 0 56 0 0
#> 163 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 103 24.00 0 56 1 0
#> 163.1 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 19 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 67 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 146.1 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 67.1 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 178.1 24.00 0 52 1 0
#> 67.2 24.00 0 25 0 0
#> 163.2 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 131 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 163.3 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 54.1 24.00 0 53 1 0
#> 3.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 162.2 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 3.2 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 144.1 24.00 0 28 0 1
#> 112.1 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 144.2 24.00 0 28 0 1
#> 138.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 172.1 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 74.1 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 172.2 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 38 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 44.1 24.00 0 56 0 0
#> 73.1 24.00 0 NA 0 1
#> 162.3 24.00 0 51 0 0
#> 162.4 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 102.1 24.00 0 49 0 0
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.15 NA NA NA
#> 2 age, Cure model 0.0232 NA NA NA
#> 3 grade_ii, Cure model -0.219 NA NA NA
#> 4 grade_iii, Cure model 0.676 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00640 NA NA NA
#> 2 grade_ii, Survival model 0.000278 NA NA NA
#> 3 grade_iii, Survival model 0.0297 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.14922 0.02317 -0.21905 0.67558
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250.3
#> Residual Deviance: 240.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.14921877 0.02317052 -0.21904521 0.67558324
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0063968946 0.0002778921 0.0297224152
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0468192639 0.9309592683 0.4755299722 0.1948845637 0.0345561329
#> [6] 0.0668044351 0.7310565468 0.9036094275 0.9172618618 0.6926789664
#> [11] 0.6548689079 0.2222110250 0.3435000799 0.0871014206 0.4196590456
#> [16] 0.1423432549 0.6548689079 0.9309592683 0.7441252035 0.2912337166
#> [21] 0.6422422786 0.1337820195 0.0120478939 0.0668044351 0.3223658463
#> [26] 0.8634708923 0.6926789664 0.7572435310 0.9859884121 0.5218413027
#> [31] 0.0042191487 0.1423432549 0.3755624186 0.5571973400 0.5571973400
#> [36] 0.9720377110 0.3435000799 0.0042191487 0.6052524933 0.3646853351
#> [41] 0.7572435310 0.5218413027 0.0871014206 0.4196590456 0.5218413027
#> [46] 0.1948845637 0.1856743212 0.1174024319 0.1174024319 0.3865254785
#> [51] 0.0233711530 0.1092564159 0.0175243768 0.8231943310 0.1676013475
#> [56] 0.0668044351 0.0233711530 0.0871014206 0.6052524933 0.1765833712
#> [61] 0.4985527325 0.8499943104 0.2415822663 0.2711404740 0.4084673396
#> [66] 0.8634708923 0.4755299722 0.8634708923 0.1423432549 0.3865254785
#> [71] 0.6926789664 0.6052524933 0.5571973400 0.5571973400 0.4528572382
#> [76] 0.4528572382 0.3328967607 0.0345561329 0.3119119801 0.2610798531
#> [81] 0.4985527325 0.0468192639 0.8098698590 0.4196590456 0.1948845637
#> [86] 0.2711404740 0.9309592683 0.0597499537 0.6548689079 0.3015268078
#> [91] 0.2318526085 0.7966030547 0.8365733415 0.7833906106 0.0008823159
#> [96] 0.2415822663 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000
#>
#> $Time
#> 194 77 100 166 15 136 81 145 187 13 133 105 111
#> 22.40 7.27 16.07 19.98 22.68 21.83 14.06 10.07 9.92 14.34 14.65 19.75 17.45
#> 197 192 90 133.1 77.1 60 8 180 99 92 136.1 41 61
#> 21.60 16.44 20.94 14.65 7.27 13.15 18.43 14.82 21.19 22.92 21.83 18.02 10.12
#> 13.1 155 127 125 164 90.1 45 29 29.1 91 111.1 164.1 157
#> 14.34 13.08 3.53 15.65 23.60 20.94 17.42 15.45 15.45 5.33 17.45 23.60 15.10
#> 30 155.1 125.1 197.1 85 125.2 166.1 150 153 153.1 130 63 139
#> 17.43 13.08 15.65 21.60 16.44 15.65 19.98 20.33 21.33 21.33 16.47 22.77 21.49
#> 113 159 32 136.2 63.1 197.2 157.1 190 26 52 55 179 181
#> 22.86 10.55 20.90 21.83 22.77 21.60 15.10 20.81 15.77 10.42 19.34 18.63 16.46
#> 61.1 100.1 61.2 90.2 130.1 13.2 157.2 29.2 29.3 188 188.1 184 15.1
#> 10.12 16.07 10.12 20.94 16.47 14.34 15.10 15.45 15.45 16.16 16.16 17.77 22.68
#> 108 97 26.1 194.1 49 85.1 166.2 179.1 77.2 175 133.2 88 170
#> 18.29 19.14 15.77 22.40 12.19 16.44 19.98 18.63 7.27 21.91 14.65 18.37 19.54
#> 42 10 14 168 58 146 87 162 144 94 11 54 34
#> 12.43 10.53 12.89 23.72 19.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 186 1.1 173 20 143 74 172 120 137 82 44 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 103 163.1 112 196 19 3 22 178 11.1 67 53 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 146.1 162.1 67.1 193 178.1 67.2 163.2 198 160 103.1 131 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 102 163.3 196.1 54.1 3.1 138 132 162.2 121 135 3.2 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 112.1 17 72 65 200 144.2 138.1 151 172.1 80.1 74.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 165 172.2 116.1 38 191 44.1 162.3 162.4 94.1 102.1 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007318097 0.498790020 0.199473025
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.344297276 0.008503734 -0.222846957
#> grade_iii, Cure model
#> 0.614717900
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 85 16.44 1 36 0 0
#> 88 18.37 1 47 0 0
#> 86 23.81 1 58 0 1
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 81 14.06 1 34 0 0
#> 108 18.29 1 39 0 1
#> 167.1 15.55 1 56 1 0
#> 150 20.33 1 48 0 0
#> 175 21.91 1 43 0 0
#> 23 16.92 1 61 0 0
#> 15 22.68 1 48 0 0
#> 36 21.19 1 48 0 1
#> 149 8.37 1 33 1 0
#> 32 20.90 1 37 1 0
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 157 15.10 1 47 0 0
#> 124.1 9.73 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 85.1 16.44 1 36 0 0
#> 106 16.67 1 49 1 0
#> 133 14.65 1 57 0 0
#> 187 9.92 1 39 1 0
#> 111 17.45 1 47 0 1
#> 154 12.63 1 20 1 0
#> 159 10.55 1 50 0 1
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 39.1 15.59 1 37 0 1
#> 96 14.54 1 33 0 1
#> 157.1 15.10 1 47 0 0
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 86.1 23.81 1 58 0 1
#> 99 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 40 18.00 1 28 1 0
#> 23.1 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 39.2 15.59 1 37 0 1
#> 91 5.33 1 61 0 1
#> 159.1 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 133.1 14.65 1 57 0 0
#> 89 11.44 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 194 22.40 1 38 0 1
#> 79 16.23 1 54 1 0
#> 77 7.27 1 67 0 1
#> 123.1 13.00 1 44 1 0
#> 133.2 14.65 1 57 0 0
#> 61.1 10.12 1 36 0 1
#> 93 10.33 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 171.1 16.57 1 41 0 1
#> 111.1 17.45 1 47 0 1
#> 40.1 18.00 1 28 1 0
#> 158 20.14 1 74 1 0
#> 136 21.83 1 43 0 1
#> 88.1 18.37 1 47 0 0
#> 4.1 17.64 1 NA 0 1
#> 36.1 21.19 1 48 0 1
#> 69 23.23 1 25 0 1
#> 159.2 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 125 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 77.1 7.27 1 67 0 1
#> 92 22.92 1 47 0 1
#> 101.1 9.97 1 10 0 1
#> 139 21.49 1 63 1 0
#> 4.2 17.64 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 133.3 14.65 1 57 0 0
#> 92.1 22.92 1 47 0 1
#> 107 11.18 1 54 1 0
#> 150.1 20.33 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 100 16.07 1 60 0 0
#> 197 21.60 1 69 1 0
#> 171.2 16.57 1 41 0 1
#> 195 11.76 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 175.1 21.91 1 43 0 0
#> 124.2 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 23.2 16.92 1 61 0 0
#> 93.1 10.33 1 52 0 1
#> 101.2 9.97 1 10 0 1
#> 136.1 21.83 1 43 0 1
#> 90 20.94 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 167.2 15.55 1 56 1 0
#> 107.1 11.18 1 54 1 0
#> 6 15.64 1 39 0 0
#> 56 12.21 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 187.1 9.92 1 39 1 0
#> 175.2 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 188 16.16 1 46 0 1
#> 29.2 15.45 1 68 1 0
#> 24.1 23.89 1 38 0 0
#> 164 23.60 1 76 0 1
#> 117 17.46 1 26 0 1
#> 7 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 126 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 95 24.00 0 68 0 1
#> 151.1 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 146 24.00 0 63 1 0
#> 33.1 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 193.1 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 95.1 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 38 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 163 24.00 0 66 0 0
#> 112.1 24.00 0 61 0 0
#> 173.1 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 135.2 24.00 0 58 1 0
#> 67 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 135.3 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 160.1 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 71 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 47 24.00 0 38 0 1
#> 9.2 24.00 0 31 1 0
#> 65.1 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 94 24.00 0 51 0 1
#> 47.1 24.00 0 38 0 1
#> 126.1 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 165 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 146.1 24.00 0 63 1 0
#> 47.2 24.00 0 38 0 1
#> 95.2 24.00 0 68 0 1
#> 53.1 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 156.1 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 83.1 24.00 0 6 0 0
#> 191.1 24.00 0 60 0 1
#> 135.4 24.00 0 58 1 0
#> 54 24.00 0 53 1 0
#> 72.2 24.00 0 40 0 1
#> 71.1 24.00 0 51 0 0
#> 38.2 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 12.1 24.00 0 63 0 0
#> 112.2 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 53.2 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.344 NA NA NA
#> 2 age, Cure model 0.00850 NA NA NA
#> 3 grade_ii, Cure model -0.223 NA NA NA
#> 4 grade_iii, Cure model 0.615 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00732 NA NA NA
#> 2 grade_ii, Survival model 0.499 NA NA NA
#> 3 grade_iii, Survival model 0.199 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.344297 0.008504 -0.222847 0.614718
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.344297276 0.008503734 -0.222846957 0.614717900
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007318097 0.498790020 0.199473025
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.301884327 0.456073103 0.311483027 0.015354176 0.576762173 0.718939527
#> [7] 0.330724713 0.576762173 0.237058459 0.102243886 0.388098398 0.084841643
#> [13] 0.173777199 0.948179570 0.209945602 0.546624761 0.740001595 0.636744692
#> [19] 0.283114754 0.729457389 0.456073103 0.417100817 0.657086141 0.906651213
#> [25] 0.369034421 0.760825865 0.802470944 0.037959549 0.227949022 0.546624761
#> [31] 0.697990239 0.636744692 0.475887680 0.516128711 0.015354176 0.173777199
#> [37] 0.927417361 0.164539663 0.340513536 0.388098398 0.426966208 0.546624761
#> [43] 0.989550412 0.802470944 0.606754141 0.657086141 0.854527189 0.264658454
#> [49] 0.264658454 0.093511889 0.485934020 0.968809256 0.740001595 0.657086141
#> [55] 0.854527189 0.833573874 0.948179570 0.426966208 0.369034421 0.340513536
#> [61] 0.255335837 0.127916754 0.311483027 0.173777199 0.052842208 0.802470944
#> [67] 0.875512419 0.526279200 0.076426634 0.968809256 0.060879535 0.875512419
#> [73] 0.155249558 0.708455453 0.657086141 0.060879535 0.781723545 0.237058459
#> [79] 0.927417361 0.506007507 0.145938190 0.426966208 0.037959549 0.102243886
#> [85] 0.283114754 0.388098398 0.833573874 0.875512419 0.127916754 0.200531317
#> [91] 0.606754141 0.576762173 0.781723545 0.536428029 0.771249551 0.209945602
#> [97] 0.906651213 0.102243886 0.004099174 0.495957744 0.606754141 0.004099174
#> [103] 0.029199687 0.359443684 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 8 85 88 86 167 81 108 167.1 150 175 23 15 36
#> 18.43 16.44 18.37 23.81 15.55 14.06 18.29 15.55 20.33 21.91 16.92 22.68 21.19
#> 149 32 39 123 157 55 155 85.1 106 133 187 111 154
#> 8.37 20.90 15.59 13.00 15.10 19.34 13.08 16.44 16.67 14.65 9.92 17.45 12.63
#> 159 129 190 39.1 96 157.1 5 26 86.1 99 183 153 40
#> 10.55 23.41 20.81 15.59 14.54 15.10 16.43 15.77 23.81 21.19 9.24 21.33 18.00
#> 23.1 171 39.2 91 159.1 29 133.1 61 170 170.1 194 79 77
#> 16.92 16.57 15.59 5.33 10.55 15.45 14.65 10.12 19.54 19.54 22.40 16.23 7.27
#> 123.1 133.2 61.1 93 149.1 171.1 111.1 40.1 158 136 88.1 36.1 69
#> 13.00 14.65 10.12 10.33 8.37 16.57 17.45 18.00 20.14 21.83 18.37 21.19 23.23
#> 159.2 101 125 113 77.1 92 101.1 139 57 133.3 92.1 107 150.1
#> 10.55 9.97 15.65 22.86 7.27 22.92 9.97 21.49 14.46 14.65 22.92 11.18 20.33
#> 183.1 100 197 171.2 129.1 175.1 58 23.2 93.1 101.2 136.1 90 29.1
#> 9.24 16.07 21.60 16.57 23.41 21.91 19.34 16.92 10.33 9.97 21.83 20.94 15.45
#> 167.2 107.1 6 56 32.1 187.1 175.2 24 188 29.2 24.1 164 117
#> 15.55 11.18 15.64 12.21 20.90 9.92 21.91 23.89 16.16 15.45 23.89 23.60 17.46
#> 7 2 135 151 126 172 112 118 80 135.1 160 33 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 151.1 193 83 146 33.1 198 193.1 82 9 191 132 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 38 38.1 141 48 20 173 163 112.1 173.1 147 156 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.2 67 9.1 118.1 27 174 116 138 135.3 65 28 186 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 121 98 71 147.1 47 9.2 65.1 119 87 94 47.1 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 165 11 146.1 47.2 95.2 53.1 64 156.1 72.1 83.1 191.1 135.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 72.2 71.1 38.2 12 12.1 112.2 102 53.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01569034 1.06108539 0.56169659
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.55201642 0.01539213 -0.63130376
#> grade_iii, Cure model
#> 0.62759677
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 99 21.19 1 38 0 1
#> 166 19.98 1 48 0 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 92 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 195 11.76 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 140 12.68 1 59 1 0
#> 150 20.33 1 48 0 0
#> 101 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 43 12.10 1 61 0 1
#> 42 12.43 1 49 0 1
#> 134.1 17.81 1 47 1 0
#> 100.1 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 181 16.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 45 17.42 1 54 0 1
#> 170 19.54 1 43 0 1
#> 166.1 19.98 1 48 0 0
#> 55 19.34 1 69 0 1
#> 69 23.23 1 25 0 1
#> 140.1 12.68 1 59 1 0
#> 123 13.00 1 44 1 0
#> 78 23.88 1 43 0 0
#> 90 20.94 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 60 13.15 1 38 1 0
#> 170.1 19.54 1 43 0 1
#> 30 17.43 1 78 0 0
#> 91.1 5.33 1 61 0 1
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 169 22.41 1 46 0 0
#> 79 16.23 1 54 1 0
#> 154 12.63 1 20 1 0
#> 6 15.64 1 39 0 0
#> 108 18.29 1 39 0 1
#> 111 17.45 1 47 0 1
#> 61 10.12 1 36 0 1
#> 90.1 20.94 1 50 0 1
#> 155 13.08 1 26 0 0
#> 188.2 16.16 1 46 0 1
#> 105 19.75 1 60 0 0
#> 169.1 22.41 1 46 0 0
#> 89.1 11.44 1 NA 0 0
#> 61.1 10.12 1 36 0 1
#> 78.1 23.88 1 43 0 0
#> 154.1 12.63 1 20 1 0
#> 124.1 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 90.2 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 43.1 12.10 1 61 0 1
#> 97 19.14 1 65 0 1
#> 170.2 19.54 1 43 0 1
#> 45.1 17.42 1 54 0 1
#> 111.1 17.45 1 47 0 1
#> 97.1 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 45.2 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 10 10.53 1 34 0 0
#> 170.3 19.54 1 43 0 1
#> 149 8.37 1 33 1 0
#> 168 23.72 1 70 0 0
#> 197.1 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 36 21.19 1 48 0 1
#> 166.2 19.98 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 81.1 14.06 1 34 0 0
#> 70 7.38 1 30 1 0
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 37 12.52 1 57 1 0
#> 166.3 19.98 1 48 0 0
#> 90.3 20.94 1 50 0 1
#> 188.3 16.16 1 46 0 1
#> 169.2 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 5.1 16.43 1 51 0 1
#> 110.1 17.56 1 65 0 1
#> 166.4 19.98 1 48 0 0
#> 81.2 14.06 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 30.1 17.43 1 78 0 0
#> 37.1 12.52 1 57 1 0
#> 166.5 19.98 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 113 22.86 1 34 0 0
#> 66 22.13 1 53 0 0
#> 197.2 21.60 1 69 1 0
#> 168.2 23.72 1 70 0 0
#> 154.2 12.63 1 20 1 0
#> 74 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 34 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 109 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 28 24.00 0 67 1 0
#> 38 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 193.1 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 163 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 74.1 24.00 0 43 0 1
#> 17.1 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 28.1 24.00 0 67 1 0
#> 46.1 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 28.2 24.00 0 67 1 0
#> 138.1 24.00 0 44 1 0
#> 138.2 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 148.1 24.00 0 61 1 0
#> 28.3 24.00 0 67 1 0
#> 35.1 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 84 24.00 0 39 0 1
#> 21 24.00 0 47 0 0
#> 35.2 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 83 24.00 0 6 0 0
#> 28.4 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 116.1 24.00 0 58 0 1
#> 173.1 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 35.3 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 28.5 24.00 0 67 1 0
#> 119.1 24.00 0 17 0 0
#> 185 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 1.1 24.00 0 23 1 0
#> 44 24.00 0 56 0 0
#> 21.2 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 98.1 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 138.3 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 119.2 24.00 0 17 0 0
#> 3 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 94.1 24.00 0 51 0 1
#> 34.1 24.00 0 36 0 0
#> 83.1 24.00 0 6 0 0
#> 27 24.00 0 63 1 0
#> 73.1 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.552 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model -0.631 NA NA NA
#> 4 grade_iii, Cure model 0.628 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0157 NA NA NA
#> 2 grade_ii, Survival model 1.06 NA NA NA
#> 3 grade_iii, Survival model 0.562 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55202 0.01539 -0.63130 0.62760
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.55201642 0.01539213 -0.63130376 0.62759677
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01569034 1.06108539 0.56169659
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1003868117 0.1855641686 0.5320011601 0.5320011601 0.3566533355
#> [6] 0.5773241869 0.0198933561 0.9771039856 0.0102852866 0.1611170834
#> [11] 0.3772235538 0.7462624799 0.1691242432 0.9194147323 0.8379967707
#> [16] 0.8610360297 0.8265894928 0.3566533355 0.5773241869 0.1531049841
#> [21] 0.4859415764 0.3249793374 0.4413395268 0.2471067677 0.1855641686
#> [26] 0.2845550994 0.0152213869 0.7462624799 0.7341600861 0.0003267236
#> [31] 0.1227625139 0.6493188398 0.6979231142 0.2471067677 0.4193859137
#> [36] 0.9771039856 0.0924560934 0.9656761047 0.0416980243 0.5204404817
#> [41] 0.7701596404 0.6010279742 0.3354700429 0.3982146903 0.8960413518
#> [46] 0.1227625139 0.7219675015 0.5320011601 0.2373312480 0.0416980243
#> [51] 0.8960413518 0.0003267236 0.7701596404 0.2945590597 0.0702675725
#> [56] 0.1227625139 0.6131092261 0.8610360297 0.3046481674 0.2471067677
#> [61] 0.4413395268 0.3982146903 0.3046481674 0.6251918763 0.1003868117
#> [66] 0.0300463532 0.4413395268 0.6614317467 0.0300463532 0.8842784294
#> [71] 0.2471067677 0.9311020535 0.0023274496 0.0702675725 0.4974556070
#> [76] 0.6371957869 0.3459768692 0.1003868117 0.1855641686 0.1691242432
#> [81] 0.6614317467 0.9426844563 0.4744641155 0.6979231142 0.8039903088
#> [86] 0.1855641686 0.1227625139 0.5320011601 0.0416980243 0.9541534726
#> [91] 0.4974556070 0.3772235538 0.1855641686 0.6614317467 0.0023274496
#> [96] 0.4193859137 0.8039903088 0.1855641686 0.8379967707 0.0247539612
#> [101] 0.0620070023 0.0702675725 0.0023274496 0.7701596404 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 99 166 188 188.1 134 100 92 91 164 128 110 140 150
#> 21.19 19.98 16.16 16.16 17.81 16.07 22.92 5.33 23.60 20.35 17.56 12.68 20.33
#> 101 56 43 42 134.1 100.1 190 181 179 45 170 166.1 55
#> 9.97 12.21 12.10 12.43 17.81 16.07 20.81 16.46 18.63 17.42 19.54 19.98 19.34
#> 69 140.1 123 78 90 96 60 170.1 30 91.1 153 25 169
#> 23.23 12.68 13.00 23.88 20.94 14.54 13.15 19.54 17.43 5.33 21.33 6.32 22.41
#> 79 154 6 108 111 61 90.1 155 188.2 105 169.1 61.1 78.1
#> 16.23 12.63 15.64 18.29 17.45 10.12 20.94 13.08 16.16 19.75 22.41 10.12 23.88
#> 154.1 76 197 90.2 29 43.1 97 170.2 45.1 111.1 97.1 18 99.1
#> 12.63 19.22 21.60 20.94 15.45 12.10 19.14 19.54 17.42 17.45 19.14 15.21 21.19
#> 15 45.2 81 15.1 10 170.3 149 168 197.1 5 157 51 36
#> 22.68 17.42 14.06 22.68 10.53 19.54 8.37 23.72 21.60 16.43 15.10 18.23 21.19
#> 166.2 150.1 81.1 70 23 60.1 37 166.3 90.3 188.3 169.2 77 5.1
#> 19.98 20.33 14.06 7.38 16.92 13.15 12.52 19.98 20.94 16.16 22.41 7.27 16.43
#> 110.1 166.4 81.2 168.1 30.1 37.1 166.5 56.1 113 66 197.2 168.2 154.2
#> 17.56 19.98 14.06 23.72 17.43 12.52 19.98 12.21 22.86 22.13 21.60 23.72 12.63
#> 74 131 132 102 34 126 109 156 46 173 54 28 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 138 148 193 193.1 2 163 11 48 17 74.1 17.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 95 35 94 28.1 46.1 22 28.2 138.1 138.2 48.1 104 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 116 120 1 20 98 148.1 28.3 35.1 163.1 7.1 84 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.2 119 83 28.4 178 116.1 173.1 137 35.3 21.1 28.5 119.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 1.1 44 21.2 122 126.1 98.1 118 44.1 138.3 53 103 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 119.2 3 147 94.1 34.1 83.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0186543 0.3497771 1.0347924
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.78984243 0.01512941 -0.30651465
#> grade_iii, Cure model
#> 0.96838174
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 150 20.33 1 48 0 0
#> 5 16.43 1 51 0 1
#> 63 22.77 1 31 1 0
#> 76 19.22 1 54 0 1
#> 153 21.33 1 55 1 0
#> 194 22.40 1 38 0 1
#> 129 23.41 1 53 1 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 171 16.57 1 41 0 1
#> 154 12.63 1 20 1 0
#> 13 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 13.1 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 175 21.91 1 43 0 0
#> 117 17.46 1 26 0 1
#> 168 23.72 1 70 0 0
#> 111.1 17.45 1 47 0 1
#> 41.1 18.02 1 40 1 0
#> 99 21.19 1 38 0 1
#> 128 20.35 1 35 0 1
#> 175.1 21.91 1 43 0 0
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 139 21.49 1 63 1 0
#> 189.1 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 123 13.00 1 44 1 0
#> 170 19.54 1 43 0 1
#> 192 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 166 19.98 1 48 0 0
#> 68 20.62 1 44 0 0
#> 99.1 21.19 1 38 0 1
#> 96.1 14.54 1 33 0 1
#> 179 18.63 1 42 0 0
#> 18 15.21 1 49 1 0
#> 167 15.55 1 56 1 0
#> 77.1 7.27 1 67 0 1
#> 41.2 18.02 1 40 1 0
#> 170.1 19.54 1 43 0 1
#> 76.1 19.22 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 111.2 17.45 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 13.2 14.34 1 54 0 1
#> 51 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 195.1 11.76 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 158 20.14 1 74 1 0
#> 40 18.00 1 28 1 0
#> 57 14.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 68.1 20.62 1 44 0 0
#> 58 19.34 1 39 0 0
#> 66 22.13 1 53 0 0
#> 45 17.42 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 89.1 11.44 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 130 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 23.1 16.92 1 61 0 0
#> 139.1 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 69.1 23.23 1 25 0 1
#> 177 12.53 1 75 0 0
#> 129.1 23.41 1 53 1 0
#> 57.1 14.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 37 12.52 1 57 1 0
#> 111.3 17.45 1 47 0 1
#> 89.2 11.44 1 NA 0 0
#> 63.1 22.77 1 31 1 0
#> 58.1 19.34 1 39 0 0
#> 180 14.82 1 37 0 0
#> 117.1 17.46 1 26 0 1
#> 77.2 7.27 1 67 0 1
#> 108 18.29 1 39 0 1
#> 63.2 22.77 1 31 1 0
#> 23.2 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 170.2 19.54 1 43 0 1
#> 189.2 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 110 17.56 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 181.1 16.46 1 45 0 1
#> 13.3 14.34 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 88.1 18.37 1 47 0 0
#> 11 24.00 0 42 0 1
#> 200 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 119 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 48 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 135 24.00 0 58 1 0
#> 118 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 135.1 24.00 0 58 1 0
#> 138.1 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 22 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 67 24.00 0 25 0 0
#> 102 24.00 0 49 0 0
#> 176 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 71.1 24.00 0 51 0 0
#> 31.2 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 27.1 24.00 0 63 1 0
#> 193.1 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 144 24.00 0 28 0 1
#> 21 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 142 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 71.2 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 1.1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 144.1 24.00 0 28 0 1
#> 34 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 82 24.00 0 34 0 0
#> 84.1 24.00 0 39 0 1
#> 156.1 24.00 0 50 1 0
#> 64.1 24.00 0 43 0 0
#> 174.1 24.00 0 49 1 0
#> 12.1 24.00 0 63 0 0
#> 7.2 24.00 0 37 1 0
#> 102.1 24.00 0 49 0 0
#> 121 24.00 0 57 1 0
#> 138.2 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 20 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 138.3 24.00 0 44 1 0
#> 135.2 24.00 0 58 1 0
#> 20.1 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 54.1 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.790 NA NA NA
#> 2 age, Cure model 0.0151 NA NA NA
#> 3 grade_ii, Cure model -0.307 NA NA NA
#> 4 grade_iii, Cure model 0.968 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0187 NA NA NA
#> 2 grade_ii, Survival model 0.350 NA NA NA
#> 3 grade_iii, Survival model 1.03 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.78984 0.01513 -0.30651 0.96838
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.9
#> Residual Deviance: 245.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.78984243 0.01512941 -0.30651465 0.96838174
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0186543 0.3497771 1.0347924
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8418507 0.7396962 0.9204925 0.5346370 0.8027666 0.6654573 0.5805628
#> [8] 0.4509592 0.4987868 0.9144125 0.8985741 0.9733014 0.9614892 0.8707856
#> [15] 0.9292228 0.9614892 0.9979342 0.6331127 0.8884443 0.6079275 0.8629228
#> [22] 0.4155104 0.8707856 0.8418507 0.6753808 0.7251306 0.6079275 0.9916463
#> [29] 0.2008727 0.6448564 0.9511891 0.9234754 0.9709423 0.7740114 0.9144125
#> [36] 0.9803090 0.7606738 0.7091504 0.6753808 0.9511891 0.8181517 0.9431159
#> [43] 0.9376422 0.9916463 0.8418507 0.7740114 0.8027666 0.7396962 0.9320482
#> [50] 0.9871886 0.2008727 0.8707856 0.9234754 0.9614892 0.8374436 0.7251306
#> [57] 0.9894212 0.9082818 0.9348645 0.7538580 0.8546060 0.9564156 0.9826142
#> [64] 0.3286111 0.7091504 0.7913464 0.5945108 0.8849705 0.7674024 0.8985741
#> [71] 0.9485102 0.9050923 0.9849066 0.8884443 0.6448564 0.9403952 0.4987868
#> [78] 0.9756545 0.4509592 0.9564156 0.8131921 0.9779904 0.8707856 0.5346370
#> [85] 0.7913464 0.9458169 0.8629228 0.9916463 0.8327331 0.5346370 0.8884443
#> [92] 0.6926986 0.7740114 0.8230759 0.8588495 0.6926986 0.9082818 0.9614892
#> [99] 0.3286111 0.8230759 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 41 150 5 63 76 153 194 129 69 85 171 154 13
#> 18.02 20.33 16.43 22.77 19.22 21.33 22.40 23.41 23.23 16.44 16.57 12.63 14.34
#> 111 26 13.1 127 197 23 175 117 168 111.1 41.1 99 128
#> 17.45 15.77 14.34 3.53 21.60 16.92 21.91 17.46 23.72 17.45 18.02 21.19 20.35
#> 175.1 77 24 139 96 188 123 170 192 49 166 68 99.1
#> 21.91 7.27 23.89 21.49 14.54 16.16 13.00 19.54 16.44 12.19 19.98 20.62 21.19
#> 96.1 179 18 167 77.1 41.2 170.1 76.1 150.1 6 16 24.1 111.2
#> 14.54 18.63 15.21 15.55 7.27 18.02 19.54 19.22 20.33 15.64 8.71 23.89 17.45
#> 188.1 13.2 51 128.1 70 181 39 158 40 57 101 78 68.1
#> 16.16 14.34 18.23 20.35 7.38 16.46 15.59 20.14 18.00 14.46 9.97 23.88 20.62
#> 58 66 45 105 171.1 133 130 187 23.1 139.1 29 69.1 177
#> 19.34 22.13 17.42 19.75 16.57 14.65 16.47 9.92 16.92 21.49 15.45 23.23 12.53
#> 129.1 57.1 97 37 111.3 63.1 58.1 180 117.1 77.2 108 63.2 23.2
#> 23.41 14.46 19.14 12.52 17.45 22.77 19.34 14.82 17.46 7.27 18.29 22.77 16.92
#> 190 170.2 88 110 190.1 181.1 13.3 78.1 88.1 11 200 196 119
#> 20.81 19.54 18.37 17.56 20.81 16.46 14.34 23.88 18.37 24.00 24.00 24.00 24.00
#> 182 7 48 138 120 116 135 118 182.1 135.1 138.1 198 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 193 98 22 62 1 67 102 176 71 31 31.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 173 44 71.1 31.2 172 165 28 27.1 193.1 2 144 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 178 178.1 196.1 142 156 3 182.2 71.2 67.1 7.1 64 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 112 144.1 34 147 65 116.1 82 84.1 156.1 64.1 174.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.2 102.1 121 138.2 17 53 20 143 138.3 135.2 20.1 94 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 160 156.2 152 147.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00525467 1.06452241 0.60616201
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.549613362 0.004377977 0.469844394
#> grade_iii, Cure model
#> 1.001339054
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x564823521e00>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 93 10.33 1 52 0 1
#> 13 14.34 1 54 0 1
#> 26 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 194 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 6 15.64 1 39 0 0
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 70 7.38 1 30 1 0
#> 192 16.44 1 31 1 0
#> 194.1 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 78 23.88 1 43 0 0
#> 136 21.83 1 43 0 1
#> 78.1 23.88 1 43 0 0
#> 77 7.27 1 67 0 1
#> 199 19.81 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 45 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 52 10.42 1 52 0 1
#> 29 15.45 1 68 1 0
#> 61 10.12 1 36 0 1
#> 171 16.57 1 41 0 1
#> 58 19.34 1 39 0 0
#> 108 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 139 21.49 1 63 1 0
#> 4 17.64 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 105 19.75 1 60 0 0
#> 188 16.16 1 46 0 1
#> 170 19.54 1 43 0 1
#> 96 14.54 1 33 0 1
#> 51.1 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 106.1 16.67 1 49 1 0
#> 97.1 19.14 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 166.1 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 113 22.86 1 34 0 0
#> 157 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 177 12.53 1 75 0 0
#> 43 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 199.1 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 81 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 70.1 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 26.2 15.77 1 49 0 1
#> 79.1 16.23 1 54 1 0
#> 159.1 10.55 1 50 0 1
#> 37 12.52 1 57 1 0
#> 199.2 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 124 9.73 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 117 17.46 1 26 0 1
#> 90.1 20.94 1 50 0 1
#> 158.1 20.14 1 74 1 0
#> 124.1 9.73 1 NA 1 0
#> 70.2 7.38 1 30 1 0
#> 86.1 23.81 1 58 0 1
#> 154.1 12.63 1 20 1 0
#> 96.2 14.54 1 33 0 1
#> 15 22.68 1 48 0 0
#> 70.3 7.38 1 30 1 0
#> 6.1 15.64 1 39 0 0
#> 127 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 183.2 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 155.1 13.08 1 26 0 0
#> 16 8.71 1 71 0 1
#> 159.2 10.55 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 111 17.45 1 47 0 1
#> 92.1 22.92 1 47 0 1
#> 140 12.68 1 59 1 0
#> 190 20.81 1 42 1 0
#> 13.1 14.34 1 54 0 1
#> 167 15.55 1 56 1 0
#> 86.2 23.81 1 58 0 1
#> 140.1 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 78.2 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 166.2 19.98 1 48 0 0
#> 51.2 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 164 23.60 1 76 0 1
#> 136.1 21.83 1 43 0 1
#> 113.1 22.86 1 34 0 0
#> 169.1 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 120 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 121 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 22.1 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 12.1 24.00 0 63 0 0
#> 165 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 165.1 24.00 0 47 0 0
#> 84.1 24.00 0 39 0 1
#> 173 24.00 0 19 0 1
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 121.2 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 112 24.00 0 61 0 0
#> 132 24.00 0 55 0 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 120.1 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 33.1 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 28 24.00 0 67 1 0
#> 1.1 24.00 0 23 1 0
#> 132.1 24.00 0 55 0 0
#> 84.2 24.00 0 39 0 1
#> 178.1 24.00 0 52 1 0
#> 33.2 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 141.1 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 71 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 131.1 24.00 0 66 0 0
#> 120.2 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 198.1 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 28.1 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 53 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 84.3 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 200.1 24.00 0 64 0 0
#> 116.1 24.00 0 58 0 1
#> 151.1 24.00 0 42 0 0
#> 74.1 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 165.2 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 34 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 120.3 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.550 NA NA NA
#> 2 age, Cure model 0.00438 NA NA NA
#> 3 grade_ii, Cure model 0.470 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00525 NA NA NA
#> 2 grade_ii, Survival model 1.06 NA NA NA
#> 3 grade_iii, Survival model 0.606 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.549613 0.004378 0.469844 1.001339
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 255.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.549613362 0.004377977 0.469844394 1.001339054
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00525467 1.06452241 0.60616201
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.64503822 0.90171381 0.76401469 0.66961666 0.39125001 0.59238154
#> [7] 0.27645938 0.25102377 0.79437065 0.10920376 0.69354614 0.41160894
#> [13] 0.53727656 0.56500450 0.95562928 0.63653784 0.25102377 0.61053444
#> [19] 0.01957936 0.28960938 0.01957936 0.98092116 0.40140069 0.43086213
#> [25] 0.82414503 0.60148404 0.34922889 0.89477618 0.71765934 0.91545252
#> [31] 0.62786801 0.47960788 0.51844705 0.87406127 0.32640509 0.48947846
#> [37] 0.45984561 0.66141955 0.46977481 0.74118841 0.53727656 0.49927390
#> [43] 0.61053444 0.49927390 0.66961666 0.43086213 0.92913581 0.92913581
#> [49] 0.16914276 0.73336843 0.19749052 0.83846580 0.85993510 0.22423025
#> [55] 0.92232108 0.77919341 0.98729420 0.95562928 0.06857925 0.66961666
#> [61] 0.64503822 0.87406127 0.84567717 0.78683233 0.74118841 0.57420895
#> [67] 0.34922889 0.41160894 0.95562928 0.06857925 0.82414503 0.74118841
#> [73] 0.21076575 0.95562928 0.69354614 0.99365367 0.14156019 0.92913581
#> [79] 0.33804256 0.85281857 0.79437065 0.94898011 0.87406127 0.51844705
#> [85] 0.58332583 0.14156019 0.80941205 0.38115341 0.76401469 0.70966141
#> [91] 0.06857925 0.80941205 0.37068951 0.01957936 0.86703222 0.90171381
#> [97] 0.43086213 0.53727656 0.31430062 0.12561948 0.28960938 0.16914276
#> [103] 0.22423025 0.72556665 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 79 93 13 26 68 30 175 194 155 168 6 158 51
#> 16.23 10.33 14.34 15.77 20.62 17.43 21.91 22.40 13.08 23.72 15.64 20.14 18.23
#> 134 70 192 194.1 106 78 136 78.1 77 150 166 154 45
#> 17.81 7.38 16.44 22.40 16.67 23.88 21.83 23.88 7.27 20.33 19.98 12.63 17.42
#> 90 52 29 61 171 58 108 159 139 76 105 188 170
#> 20.94 10.42 15.45 10.12 16.57 19.34 18.29 10.55 21.49 19.22 19.75 16.16 19.54
#> 96 51.1 97 106.1 97.1 26.1 166.1 183 183.1 113 157 63 177
#> 14.54 18.23 19.14 16.67 19.14 15.77 19.98 9.24 9.24 22.86 15.10 22.77 12.53
#> 43 169 145 81 91 70.1 86 26.2 79.1 159.1 37 60 96.1
#> 12.10 22.41 10.07 14.06 5.33 7.38 23.81 15.77 16.23 10.55 12.52 13.15 14.54
#> 117 90.1 158.1 70.2 86.1 154.1 96.2 15 70.3 6.1 127 92 183.2
#> 17.46 20.94 20.14 7.38 23.81 12.63 14.54 22.68 7.38 15.64 3.53 22.92 9.24
#> 153 42 155.1 16 159.2 108.1 111 92.1 140 190 13.1 167 86.2
#> 21.33 12.43 13.08 8.71 10.55 18.29 17.45 22.92 12.68 20.81 14.34 15.55 23.81
#> 140.1 32 78.2 107 93.1 166.2 51.2 197 164 136.1 113.1 169.1 18
#> 12.68 20.90 23.88 11.18 10.33 19.98 18.23 21.60 23.60 21.83 22.86 22.41 15.21
#> 120 116 121 22 162 162.1 121.1 22.1 102 12 12.1 165 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 141 146 102.1 165.1 84.1 173 200 178 1 185 121.2 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 131 33 82 112 132 122 135 120.1 174 33.1 151 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 1.1 132.1 84.2 178.1 33.2 46 141.1 193 71 20 38 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 120.2 94 198.1 74 11 28.1 3 126 103 53 38.1 84.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 200.1 116.1 151.1 74.1 143 9 176 186 163 98 165.2 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 31 31.1 2 34 44 17 27 120.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>